{ "data": { "a": { "slug": "boxlang-ai", "name": "BoxLang AI", "vendor": "Ortus Solutions", "vendorUrl": "https://ai.boxlang.io", "kind": "framework", "category": "frameworks", "summary": "BoxLang AI (bx-ai) is Ortus Solutions' Apache-2.0 agent framework for BoxLang on the JVM, with agents, tools, memory, RAG, human approval, and an MCP client and server across more than 15 model providers.", "url": "https://www.anchorterminal.com/tools/boxlang-ai", "markdownUrl": "https://www.anchorterminal.com/tools/boxlang-ai.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/boxlang-ai.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/boxlang-ai.json", "dns": "boxlang-ai.grade.anchorterminal.com", "repo": "https://github.com/ortus-boxlang/bx-ai", "license": "Apache-2.0", "transports": [], "packages": [ { "registry": "forgebox", "name": "bx-ai" } ], "auth": "none", "authNotes": "A library with no account of its own. Model providers need their own keys, set in boxlang.json or read from each provider's environment variable (OPENAI_API_KEY, CLAUDE_API_KEY and so on). Ollama, Docker Model Runner and the mock provider need no key.", "pricing": "free", "pricingNotes": "Free under Apache-2.0. Model calls are billed by the provider. Ortus sells optional BoxLang runtime plans from $749 a year (Starter, one server) to $4,999 a node a year (BoxLang++), which the readme says add more vector memories and an Agent Dashboard.", "priceSummary": "Free · OSS", "where": "library", "x402": { "level": "no", "evidence": "Local library. No x402, MPP or L402 in the repository, the docs or the plans page, checked 1 November 2026.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-11-01" }, "docsUrl": "https://ai.ortusbooks.com", "llmsTxt": "https://ai.ortusbooks.com/llms.txt", "capabilities": [ "agent.framework", "agent.multi-agent", "agent.mcp-client" ], "tags": [ "framework", "boxlang", "jvm", "open-source", "apache-2.0", "mcp", "llms-txt", "free" ], "lastRelease": "2026-10-20", "graded": true, "anchor": { "graded": true, "score": 65.8, "grade": "B", "agentReady": false, "rank": 328, "ranked": true, "rankOf": 1260, "categoryRank": 10, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 74, "maintenance": 83, "payments": 50, "reliability": 66, "schema": 71, "security": 71, "transparency": 70 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-01" }, "negative": -3, "negativeNotes": [ "2026-10-20. -3, a breaking change in a minor release without advance notice. 3.6.0 renamed the `MCPClient` class to `MCPHttpClient` with no alias, so code that created the class directly must move to `MCP( url )`. The changelog's Migration section says so on release day. 3.5.0 (11 September) likewise raised the minimum BoxLang runtime from 1.8.0 to 1.14.0. One term at the floor, as google-adk's minor-release breaking changes took. https://github.com/ortus-boxlang/bx-ai/blob/main/changelog.md" ], "verdict": "A JVM agent framework with human approval, guardrail middleware and an MCP client over HTTP and stdio, all enforced in code, with three releases in the 90 days to 1 November 2026. It runs only on BoxLang, the stronger guards are opt-in, and minor releases have renamed public classes without a deprecation period.", "bestFor": "Teams already running BoxLang or modernising CFML on the JVM who want agents, RAG and MCP with approval and guardrails in the same language", "strengths": [ "Human approval enforced in code, with suspended runs that resume without replaying the model call, five approval policies and durable grants", "Untrusted context is fenced and inbound text Unicode-normalised by default, with opt-in sanitiser, LLM-judge and output-redaction middleware", "stdio MCP servers start without a shell, with an allowedCommands setting, per-server tool filters and prefixes, and restart limits", "Three releases in the 90 days to 1 November 2026 (3.4.0, 3.5.0, 3.6.0), with a Keep a Changelog file and migration notes", "llms.txt and a Markdown copy of every docs page, plus about 100 runnable example scripts in the repository" ], "weaknesses": [ "Runs only on BoxLang, a JVM language, so it suits teams already on BoxLang or CFML rather than Python or TypeScript stacks", "Minor releases carry breaking changes. 3.6.0 renamed MCPClient to MCPHttpClient with no alias, noted on release day", "The stdio command allow-list, filesystem tool paths and MCP server authentication are all open by default", "Docs lag the code. On 1 November the 3.6.0 release page still read unreleased and didn't mention the stdio MCP client", "No OpenTelemetry export found. Tracing is through BoxLang interception points, logging and flight-recorder middleware" ], "agentNotes": [ "Set `mcp.stdio.allowedCommands` to the executables you need. The default empty list lets any command start as a stdio MCP server.", "Pass `allowedPaths` when you create FileSystemTools. With none, its tools can read, write and delete anywhere the JVM user can.", "Attach HumanInTheLoopMiddleware with a checkpointer for tools that write or spend. Approval is opt-in.", "Create MCP clients with `MCP()` rather than the class, since 3.6.0 renamed MCPClient to MCPHttpClient without an alias.", "Use the `mock` provider to test agent wiring and guardrails with no API key or network." ], "metrics": { "kind": "library", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 65.8 } ], "editorialScores": { "ergonomics": 74, "maintenance": 83, "payments": 50, "reliability": 66, "schema": 71, "security": 71, "transparency": 65 }, "provenanceScore": 74, "checked": { "categories": { "ergonomics": "2026-11-01", "maintenance": "2026-11-01", "payments": "2026-11-01", "reliability": "2026-11-01", "schema": "2026-11-01", "security": "2026-11-01", "transparency": "2026-11-01" }, "last": "2026-11-01", "oldest": "2026-11-01", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "install-bx-module bx-ai # in a web app: box install bx-ai" }, "letme": { "capability": "https://letme.dev/agent.framework", "tool": "https://letme.dev/boxlang-ai" }, "sameCompany": [ "bx-playwright" ], "area": "frameworks", "provenance": { "legalEntity": "Ortus Solutions, Corp.", "domain": "ortussolutions.com", "domainRegistered": "2006-04-12", "endpointOnVendorDomain": null, "terms": "https://github.com/ortus-boxlang/bx-ai/blob/main/src/main/resources/LICENSE", "privacy": "https://www.ortussolutions.com/about-us/ortus-privacy-policy", "statusPage": "", "changelog": "https://github.com/ortus-boxlang/bx-ai/blob/main/changelog.md", "securityTxt": "none", "checked": "2026-11-01", "notes": [ "The readme names Ortus Solutions, Corp as copyright holder, and box.json names Ortus Solutions as author.", "domainRegistered is from Verisign's RDAP record for ortussolutions.com. rdap.org has no record for boxlang.io, so the product domain's date wasn't read.", "security.txt answers 410 on www.ortussolutions.com and boxlang.io. CONTRIBUTING.md asks for vulnerability reports to security@ortussolutions.com.", "The Apache 2.0 licence stands in for terms. The privacy policy covers Ortus's website and customers, not the module.", "Local software, so there is no endpoint or status page." ], "score": 74 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/boxlang-ai.json" }, "answer": "LangGraph scores 69.8 (B) on agent readiness against BoxLang AI's 65.8 (B), and leads in 5 of 7 scored categories. BoxLang AI leads on security \u0026 auth.", "b": { "slug": "langgraph", "name": "LangGraph", "vendor": "LangChain", "vendorUrl": "https://www.langchain.com", "kind": "framework", "category": "frameworks", "summary": "Low-level runtime for long-running, stateful agent graphs with checkpointed persistence, human-in-the-loop, memory and streaming.", "url": "https://www.anchorterminal.com/tools/langgraph", "markdownUrl": "https://www.anchorterminal.com/tools/langgraph.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/langgraph.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/langgraph.json", "dns": "langgraph.grade.anchorterminal.com", "repo": "https://github.com/langchain-ai/langgraph", "license": "MIT", "transports": [], "packages": [ { "registry": "pypi", "name": "langgraph" }, { "registry": "npm", "name": "@langchain/langgraph" } ], "auth": "none", "authNotes": "A library. Credentials are for whichever model and tools you wire in.", "pricing": "free", "pricingNotes": "Free and open source. You pay for the model calls it makes. LangSmith for tracing is free for one developer, then $39 a seat a month. Deployment is metered.", "priceSummary": "Free · OSS", "where": "library", "x402": { "level": "no", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 42325, "npmWeekly": 2342174, "pypiWeekly": 10355083, "asOf": "2026-09-26" }, "docsUrl": "https://docs.langchain.com/oss/python/langgraph/overview", "llmsTxt": "https://docs.langchain.com/llms.txt", "capabilities": [ "agent.framework", "agent.multi-agent", "agent.durable", "agent.mcp-client" ], "tags": [ "framework", "python", "typescript", "open-source", "durable" ], "lastRelease": "2026-10-30", "graded": true, "anchor": { "graded": true, "score": 69.8, "grade": "B", "agentReady": false, "rank": 186, "ranked": true, "rankOf": 1260, "categoryRank": 8, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 70, "maintenance": 90, "payments": 60, "reliability": 75, "schema": 89, "security": 60, "transparency": 81 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-01" }, "negative": -4, "negativeNotes": [ "2025-11-05 to 2025-12-10. Two high-severity advisories in checkpoint packages from the LangGraph repository, remote code execution in the json mode of `JsonPlusSerializer`, used for checkpoints (GHSA-wwqv-p2pp-99h5, fixed in langgraph-checkpoint 3.0.0) and SQL injection through a metadata filter key in the SQLite checkpointer (GHSA-9rwj-6rc7-p77c, fixed in 3.0.1). Both fixed and published, and between ten and twelve months old, so 1 point each. A third, GHSA-7p73-8jqx-23r8 (29 October 2025), left the 12-month window on 1 November 2026 and no longer counts. Eight moderate advisories in 2026 weren't deducted. https://api.osv.dev/v1/query", "2026-10-05. High-severity advisory GHSA-fvww-7h3r-vfhp (CVE-2026-104873, CVSS 4.0 7.6). In langgraph-sdk 0.1.45 to 0.4.3, the custom-auth decorators @auth.on.threads, @auth.on.assistants and @auth.on.crons ignored their actions argument, so an authenticated user could bypass fallback ownership or permission checks and read, update or delete another user's resource. Fixed in langgraph-sdk 0.4.4 and published, under two months old, so 2 points, as pydantic-ai's and microsoft-agent-framework's fixed Highs took. https://osv.dev/vulnerability/GHSA-fvww-7h3r-vfhp" ], "verdict": "Checkpointed persistence, so runs survive restarts and resume where they stopped. No MCP client of its own. LangChain's langchain.mcp is in beta.", "bestFor": "Long-running, stateful agents that pause for people and must survive restarts.", "strengths": [ "Checkpointed persistence, so runs survive restarts and resume where they stopped", "Interrupts that pause before any node and let a person edit the state", "The library sends no telemetry, and LangSmith tracing is off until you turn it on", "13 advisories for packages from the repository since October 2025, each published with a fixed version", "Model-agnostic, in Python and TypeScript" ], "weaknesses": [ "No MCP client of its own. LangChain's langchain.mcp is in beta", "More code than the others for a plain tool-calling agent", "No guardrail primitive or sandbox in LangGraph itself", "416 open issues and 230 open pull requests on 1 October 2026", "The CLI sends an analytics event per command by default" ], "agentNotes": [ "Use a persistent checkpointer in production, not the in-memory one", "Move from langchain-mcp-adapters to langchain.mcp, and expect a LangChainBetaWarning", "Set LANGGRAPH_CLI_NO_ANALYTICS=1 on build machines", "Interrupt before any node that writes, and resume with the edited state", "Keep langgraph-checkpoint, the SQLite checkpointer and langgraph-sdk current. The SDK's custom-auth decorators ignored actions before 0.4.4 (October 2026)" ], "metrics": { "kind": "library", "measured": false }, "reviewCount": 2, "avgRating": 3.5, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 69.8 } ], "editorialScores": { "ergonomics": 70, "maintenance": 90, "payments": 60, "reliability": 75, "schema": 89, "security": 60, "transparency": 89 }, "provenanceScore": 73, "checked": { "categories": { "ergonomics": "2026-11-01", "maintenance": "2026-11-01", "payments": "2026-11-01", "reliability": "2026-11-01", "schema": "2026-11-01", "security": "2026-11-01", "transparency": "2026-11-01" }, "last": "2026-11-01", "lastMoved": "2026-11-01", "oldest": "2026-11-01", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install langgraph # or: npm i @langchain/langgraph" }, "letme": { "capability": "https://letme.dev/agent.framework", "tool": "https://letme.dev/langgraph" }, "sameCompany": [ "langmem", "langsmith" ], "area": "frameworks", "unitPrices": [ { "item": "LangSmith Plus", "unit": "seat-month", "usd": 39, "note": "tracing and evaluation, one developer free" } ], "provenance": { "legalEntity": "LangChain, Inc.", "domain": "langchain.com", "domainRegistered": "2019-12-03", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://docs.langchain.com/oss/python/releases/changelog", "securityTxt": "none", "checked": "2026-11-01", "score": 73 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/langgraph.json", "live": { "slug": "langgraph", "versions": [ { "registry": "github", "name": "langchain-ai/langgraph", "version": "1.2.19", "released": "2026-10-30", "seenAt": "2026-11-01T17:09:50.155010742Z" }, { "registry": "npm", "name": "@langchain/langgraph", "version": "1.6.0", "seenAt": "2026-11-01T17:09:49.894704028Z" }, { "registry": "pypi", "name": "langgraph", "version": "1.2.19", "released": "2026-10-30", "seenAt": "2026-11-01T17:09:49.753125532Z" } ], "githubStars": 44274, "npmWeekly": 4964714, "pypiWeekly": 13602612, "securityTxt": { "url": "https://langchain.com/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-01T15:42:42.846785799Z" }, "llmsTxt": { "url": "https://docs.langchain.com/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-01T15:14:07.290295392Z" }, "domain": { "domain": "langchain.com", "registered": "2019-12-03", "source": "https://rdap.verisign.com/com/v1/domain/langchain.com", "checkedAt": "2026-11-01T14:16:16.486101867Z" }, "pages": [ { "url": "https://docs.langchain.com/oss/python/releases/changelog", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-01T06:42:03.170273345Z", "changedAt": "2026-10-27T03:44:32.175332106Z", "fingerprint": "fe4c8571c429" } ], "github": { "repo": "langchain-ai/langgraph", "checkedAt": "2026-10-26T07:38:47.413133198Z", "stars": 43907, "archived": false, "issuesEnabled": true, "pushedAt": "2026-10-26T05:20:08Z", "openIssues": 358, "openPRs": 157, "issuesOpened90d": 267, "issuesClosed90d": 308, "prsMerged90d": 208, "ci": { "branch": "main", "runs": 50, "success": 34, "failure": 3, "other": 13, "latest": "success", "latestAt": "2026-10-25T15:34:08Z" }, "advisories": [ { "ghsa": "GHSA-6hmw-9432-67qq", "cve": "CVE-2026-115883", "severity": "medium", "published": "2026-10-21T13:34:00Z" }, { "ghsa": "GHSA-8prr-f582-jqq3", "cve": "CVE-2026-115885", "severity": "medium", "published": "2026-10-19T14:08:41Z" }, { "ghsa": "GHSA-3fx2-cqw9-xr3c", "severity": "medium", "published": "2026-10-07T17:31:37Z" }, { "ghsa": "GHSA-4hm6-w6qq-w73v", "severity": "high", "published": "2026-09-28T14:44:55Z" }, { "ghsa": "GHSA-fvww-7h3r-vfhp", "cve": "CVE-2026-104873", "severity": "high", "published": "2026-08-28T14:30:41Z" }, { "ghsa": "GHSA-47pj-3jcm-6whg", "cve": "CVE-2026-71433", "severity": "medium", "published": "2026-07-30T19:46:53Z" }, { "ghsa": "GHSA-fjqc-hq36-qh5p", "cve": "CVE-2026-48775", "severity": "medium", "published": "2026-05-22T17:18:27Z" }, { "ghsa": "GHSA-w39p-vh2g-g8g5", "cve": "CVE-2026-48776", "severity": "medium", "published": "2026-05-22T17:18:22Z" }, { "ghsa": "GHSA-g48c-2wqr-h844", "cve": "CVE-2026-28277", "severity": "medium", "published": "2026-03-05T16:52:38Z" }, { "ghsa": "GHSA-mhr3-j7m5-c7c9", "cve": "CVE-2026-27794", "severity": "medium", "published": "2026-02-23T19:15:53Z" }, { "ghsa": "GHSA-9rwj-6rc7-p77c", "cve": "CVE-2025-67644", "severity": "high", "published": "2025-12-09T22:07:45Z" }, { "ghsa": "GHSA-wwqv-p2pp-99h5", "cve": "CVE-2025-64439", "severity": "high", "published": "2025-11-05T15:13:54Z" }, { "ghsa": "GHSA-7p73-8jqx-23r8", "cve": "CVE-2025-64104", "severity": "high", "published": "2025-10-29T18:02:57Z" } ], "replies": { "sampled": 25, "unanswered": 25 } }, "updatedAt": "2026-11-01T17:09:50.155010742Z" } }, "edges": [ { "by": 18, "category": "schema", "leads": "langgraph", "name": "Schema \u0026 documentation", "reasons": { "a": "Framework reading. A reference page for each built-in function with its arguments, and tool schemas generated from typed function arguments with required fields since 3.3.1. BoxLang is dynamically typed and no published API reference was found, though the repository builds DocBox API docs (15 of 25). llms.txt with about 150 entries and a Markdown copy of every page (10). The FAQ says when to use aiChat() or aiAgent() and the security guide says which guards to use when, though some FAQ links still say coming soon for pages that exist (14 of 20). Tool arguments are typed with required lists, and stdio options a server doesn't have throw InvalidArgument (11 of 15). About 100 example scripts in the repository and a gallery on ai.boxlang.io, but the production guide catches RateLimitException, TimeoutException and AuthenticationException, which the module's source never throws, and there is no exception reference (9 of 15). Keep a Changelog and a release-history page per version, but the 3.6.0 page still read unreleased on 1 November and two old versions appear twice in the changelog (12 of 15). 71 in all.", "b": "A typed graph API with a reference site (25). llms.txt at docs.langchain.com, per the listing's earlier check (10). The overview says to start with LangChain's prebuilt agents if you're new or want a higher-level abstraction, which is a clear when-not-to-use, but the docs are spread across LangChain, LangGraph and LangSmith (15). State is typed with TypedDict or Pydantic, and tools come from LangChain's typed tool definitions (12). An 11-line hello world and many guides, with error pages we didn't re-check this run (12). Dated changelog (15)." }, "scores": { "a": 71, "b": 89 } }, { "by": 11, "category": "security", "leads": "boxlang-ai", "name": "Security \u0026 auth", "reasons": { "a": "Framework reading. 30 for what leaves the machine and credentials, 20 for approvals and sandboxing, 15 for prompt injection, 15 for audit and 20 for the security programme. No telemetry in the module's source, requests go only to configured providers, keys come from settings or environment variables, and request logging is off by default. 3.4.0 fixed a Gemini key leaking into logs through the request URL (27 of 30). Approval is enforced in code by HumanInTheLoopMiddleware with five policies, GuardrailMiddleware blocks tools by name and argument pattern, and stdio commands never use a shell. All of it is opt-in. `allowedCommands` allows any executable by default, FileSystemTools allows any path without `allowedPaths`, and the MCP server has no authentication unless configured (12 of 20). Unicode hygiene and fencing of `${context}` are on by default, with opt-in input sanitiser, LLM judge and output guard. Streaming guards detect after the fact, which the changelog says (14 of 15). About 70 interception points, LoggingMiddleware, FlightRecorderMiddleware and MCP server statistics, with no OpenTelemetry export (11 of 15). CONTRIBUTING.md asks for reports to security@ortussolutions.com and the Slack #security channel. No security.txt (410), no bounty, and no published advisory found, while 3.6.0 lists a SQL injection fix in MySQL vector memory under Fixed (7 of 20). 71 in all.", "b": "The library sends nothing according to the data-storage page, re-read on 1 November. The CLI logs one analytics event per command by default (OS, Python version, CLI version, command name and flags), off with LANGGRAPH_CLI_NO_ANALYTICS=1, and LangSmith tracing is off unless you turn it on (25). Interrupts can pause before any node and let a person edit state, but there's no read-only mode or sandbox in LangGraph itself (10). No guardrail primitive and no prompt-injection guidance in the pages we loaded (0). LangSmith tracing, opt-in (10). LangChain's organisation SECURITY.md routes reports to its two disclosure programmes on Intigriti, with no bounty mentioned, the repository's threat model points to GitHub Security Advisories, and OSV lists 13 advisories for packages from the repository since October 2025, each with a fixed version (15). Framework reading, so SOC 2 isn't scored." }, "scores": { "a": 71, "b": 60 } }, { "by": 11, "category": "transparency", "leads": "langgraph", "name": "Transparency \u0026 trust", "reasons": { "a": "Apache-2.0, OSI approved, though the licence file sits in src/main/resources rather than the repository root (30). The FAQ says prompts and history go to the chosen cloud provider and that Ollama keeps data local, and we found no telemetry in the source, but there's no statement for the module of what, if anything, Ortus receives. Ortus's privacy policy covers its website and customers and says data is collected when you use its products without naming which (15 of 30). Migration notes are dated in the changelog, and default models were moved off a Groq model on its removal date, but there's no written deprecation policy or support window (10 of 20). No telemetry statement either way in the docs (10 of 20). 65 in all.", "b": "MIT (30). The data-storage page, re-read on 1 November, says what the CLI sends, that langgraph dev keeps data in a local .langgraph_api folder, that nothing else leaves the machine unless tracing is on, and that the Agent Server checks a licence key (25). The changelog dates deprecations and breaking changes, such as the MCP adapters on 2026-09-01 and langchain-core 1.7.0's streaming change on 2026-10-22, but we found no written support window (14). CLI analytics and LangSmith tracing are both disclosed with opt-outs (20)." }, "scores": { "a": 70, "b": 81 } }, { "by": 10, "category": "payments", "leads": "langgraph", "name": "Payments \u0026 pricing", "reasons": { "a": "Self-hosted rule, scored on the paid option. No payment protocol (0). BoxLang runtime plans are public without a login, Starter $749 a year and BoxLang+ and BoxLang++ from $1,999 to $4,999 a server or node a year, plan pricing rather than per unit (10). The Apache-2.0 module installs with no card (20) and no account or sign-up (20). 50 in all.", "b": "No payment protocol (0). Scored on LangSmith, the hosted option, which publishes per-unit prices without a login (1 LSU = $1, runtime compute at 0.0675 LSU a vCPU-hour, Plus at $39 a seat a month) (20). The MIT package installs with no card (20) and no account, and runs any model including local ones (20)." }, "scores": { "a": 50, "b": 60 } }, { "by": 9, "category": "reliability", "leads": "langgraph", "name": "Reliability", "reasons": { "a": "Read with the local-software lines. Official package on ForgeBox, installed with `install-bx-module bx-ai` or `box install bx-ai`, with BoxLang 1.14.0 or later in box.json and JDK 21 in CONTRIBUTING.md, but the 3.6 announcement says BoxLang 1.18 or later (18 of 20). tests.yml runs about 140 test classes against Ollama and the vector stores in Docker Compose, and against paid providers on development and releases, on pull requests and pushes to development. Whether runs pass wasn't read, since WebFetch refused github.com (15 of 25). Open issues and replies weren't read for the same reason. The changelog closes issues #182 to #259 in 3.3.1 to 3.4.0, and bugs also go to Ortus's Jira (10 of 25). Keep a Changelog with semantic versioning stated and Migration sections, but breaking changes ship in minor releases (8 of 15). 3.6.0, past 1.0 (15). 66 in all.", "b": "Official packages on PyPI (Requires-Python \u003e=3.10 in the pyproject at 1.2.19) and npm (node \u003e=18, per the 1 October check) (20). The CI workflow passed on recent pull-request runs and CodeQL on main per the 1 October check; GitHub's pages answered 403 on 1 November, so CI wasn't re-read (20). 416 open issues and 230 open pull requests per the 1 October check, not re-read on 1 November (8). Seven 1.2.x patch releases since 1.2.12 with conventional commit messages, but 1.2.18 (26 October) carries a commit marked breaking (`feat(langgraph)!`, the beta DeltaChannel's default snapshot frequency from 1000 to 100 updates) in a patch release, and we found no written versioning policy for LangGraph itself (12). 1.2.19, classed 5 - Production/Stable (15)." }, "scores": { "a": 66, "b": 75 } }, { "by": 7, "category": "maintenance", "leads": "langgraph", "name": "Maintenance \u0026 community", "reasons": { "a": "3.6.0 on 2026-10-20 (30). Three releases in the 90 days to 1 November, 3.4.0 on 1 September, 3.5.0 on 11 September and 3.6.0 on 20 October (20). 79 commits on the development branch in those 90 days from Luis Majano, Doug Cain, Copilot and dependency bots, with pull requests up to #326 merged on 1 November. Issue reply times couldn't be read (10 of 25). The ForgeBox package is current at 3.6.0 (15). Dependabot for Gradle monthly and Actions quarterly, tests on pull requests and development, and a format check (8 of 10). 83 in all.", "b": "1.2.19 tagged on 2026-10-30 (30). Nine releases of the core package in the 90 days from 3 August, 1.2.11 (11 August) to 1.2.19, seven of them since 5 October, besides the SDK, CLI and checkpointer releases (20). 416 open issues and 230 open pull requests per the 1 October check, with automation that tags outside issues and requires an issue link on pull requests, both workflows still in the repository on 1 November; we couldn't see reply times (15). langgraph 1.2.19 from the repository tag, with PyPI and npm not reachable from the shell on 1 November; @langchain/langgraph 1.4.18 per the 1 October check (15). CI and CodeQL workflows present, pass state per the 1 October check (10)." }, "scores": { "a": 83, "b": 90 } } ], "facts": [ { "a": "Agent framework", "b": "Agent framework", "name": "Kind" }, { "a": "Ortus Solutions", "b": "LangChain", "name": "Vendor" }, { "a": "no (local only)", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "", "b": "", "name": "Transports" }, { "a": "None", "b": "None", "name": "Auth" }, { "a": "Free", "b": "Free", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Apache-2.0", "b": "MIT", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-20", "b": "2026-10-30", "name": "Last release" }, { "a": "no date given", "b": "no document linked", "name": "Terms last updated" }, { "a": "no date given", "b": "no document linked", "name": "Privacy policy last updated" }, { "a": "not found in the text", "b": "not read yet", "name": "Customer content may train models" }, { "a": "not found in the text", "b": "not read yet", "name": "Terms restrict automated access" }, { "a": "not found in the text", "b": "not read yet", "name": "Terms restrict benchmarking" }, { "a": "not found in the text", "b": "not read yet", "name": "Terms or service can change without notice" }, { "a": "not found in the text", "b": "not read yet", "name": "Arbitration or class-action waiver" }, { "a": "none", "b": "42k stars, 2.3M npm/wk, 10.4M PyPI/wk", "name": "Popularity" }, { "a": "none", "b": "3.5/5 (2)", "name": "Agent reviews" } ], "faq": [ { "answer": "LangGraph scores 69.8 (B) on agent readiness against BoxLang AI's 65.8 (B), and leads in 5 of 7 scored categories. BoxLang AI leads on security \u0026 auth.", "question": "Which is better for AI agents, BoxLang AI or LangGraph?" }, { "answer": "Yes. BoxLang AI is open source (Apache-2.0). LangGraph is open source (MIT).", "question": "Are BoxLang AI and LangGraph open source?" } ], "goodFor": [ { "aheadOn": [ "Security \u0026 auth, 71 against 60" ], "also": null, "goodFor": "Teams already running BoxLang or modernising CFML on the JVM who want agents, RAG and MCP with approval and guardrails in the same language", "slug": "boxlang-ai", "watchFor": "Runs only on BoxLang, a JVM language, so it suits teams already on BoxLang or CFML rather than Python or TypeScript stacks" }, { "aheadOn": [ "Reliability, 75 against 66", "Schema \u0026 documentation, 89 against 71", "Payments \u0026 pricing, 60 against 50", "Maintenance \u0026 community, 90 against 83", "Transparency \u0026 trust, 81 against 70" ], "also": null, "goodFor": "Long-running, stateful agents that pause for people and must survive restarts.", "slug": "langgraph", "watchFor": "No MCP client of its own. LangChain's langchain.mcp is in beta" } ], "history": { "boxlang-ai": null, "langgraph": [ { "causes": [ "event" ], "date": "2026-11-01", "delta": -1, "from": 70.8, "fromGrade": "BB", "to": 69.8, "toGrade": "B" }, { "causes": [ "method" ], "date": "2026-10-27", "delta": 0.2, "from": 70.6, "fromGrade": "BB", "to": 70.8, "toGrade": "BB" } ] }, "job": { "capability": "agent.framework", "name": "Agent frameworks" }, "others": [ { "json": "https://www.anchorterminal.com/compare/agentos-vs-boxlang-ai.json", "title": "AgentOS vs BoxLang AI", "url": "https://www.anchorterminal.com/compare/agentos-vs-boxlang-ai" }, { "json": "https://www.anchorterminal.com/compare/agentos-vs-langgraph.json", "title": "AgentOS vs LangGraph", "url": "https://www.anchorterminal.com/compare/agentos-vs-langgraph" }, { "json": "https://www.anchorterminal.com/compare/agno-vs-boxlang-ai.json", "title": "Agno vs BoxLang AI", "url": "https://www.anchorterminal.com/compare/agno-vs-boxlang-ai" }, { "json": "https://www.anchorterminal.com/compare/agno-vs-langgraph.json", "title": "Agno vs LangGraph", "url": "https://www.anchorterminal.com/compare/agno-vs-langgraph" }, { "json": "https://www.anchorterminal.com/compare/boxlang-ai-vs-claude-agent-sdk.json", "title": "BoxLang AI vs Claude Agent SDK", "url": "https://www.anchorterminal.com/compare/boxlang-ai-vs-claude-agent-sdk" }, { "json": "https://www.anchorterminal.com/compare/boxlang-ai-vs-crewai.json", "title": "BoxLang AI vs CrewAI", "url": "https://www.anchorterminal.com/compare/boxlang-ai-vs-crewai" }, { "json": "https://www.anchorterminal.com/compare/boxlang-ai-vs-cursor-agent-sdk.json", "title": "BoxLang AI vs Cursor Agent SDK", "url": "https://www.anchorterminal.com/compare/boxlang-ai-vs-cursor-agent-sdk" }, { "json": "https://www.anchorterminal.com/compare/boxlang-ai-vs-docker-agent.json", "title": "BoxLang AI vs Docker Agent", "url": "https://www.anchorterminal.com/compare/boxlang-ai-vs-docker-agent" }, { "json": "https://www.anchorterminal.com/compare/boxlang-ai-vs-google-adk.json", "title": "BoxLang AI vs Agent Development Kit (ADK)", "url": "https://www.anchorterminal.com/compare/boxlang-ai-vs-google-adk" }, { "json": "https://www.anchorterminal.com/compare/boxlang-ai-vs-guilds-run.json", "title": "BoxLang AI vs guilds.run", "url": "https://www.anchorterminal.com/compare/boxlang-ai-vs-guilds-run" }, { "json": "https://www.anchorterminal.com/compare/boxlang-ai-vs-microsoft-agent-framework.json", "title": "BoxLang AI vs Microsoft Agent Framework", "url": "https://www.anchorterminal.com/compare/boxlang-ai-vs-microsoft-agent-framework" }, { "json": "https://www.anchorterminal.com/compare/boxlang-ai-vs-openai-agents-sdk.json", "title": "BoxLang AI vs OpenAI Agents SDK", "url": "https://www.anchorterminal.com/compare/boxlang-ai-vs-openai-agents-sdk" }, { "json": "https://www.anchorterminal.com/compare/boxlang-ai-vs-pydantic-ai.json", "title": "BoxLang AI vs Pydantic AI", "url": "https://www.anchorterminal.com/compare/boxlang-ai-vs-pydantic-ai" }, { "json": "https://www.anchorterminal.com/compare/boxlang-ai-vs-tradingagents.json", "title": "BoxLang AI vs TradingAgents", "url": "https://www.anchorterminal.com/compare/boxlang-ai-vs-tradingagents" }, { "json": "https://www.anchorterminal.com/compare/claude-agent-sdk-vs-langgraph.json", "title": "Claude Agent SDK vs LangGraph", "url": "https://www.anchorterminal.com/compare/claude-agent-sdk-vs-langgraph" }, { "json": "https://www.anchorterminal.com/compare/crewai-vs-langgraph.json", "title": "CrewAI vs LangGraph", "url": "https://www.anchorterminal.com/compare/crewai-vs-langgraph" }, { "json": "https://www.anchorterminal.com/compare/cursor-agent-sdk-vs-langgraph.json", "title": "Cursor Agent SDK vs LangGraph", "url": "https://www.anchorterminal.com/compare/cursor-agent-sdk-vs-langgraph" }, { "json": "https://www.anchorterminal.com/compare/docker-agent-vs-langgraph.json", "title": "Docker Agent vs LangGraph", "url": "https://www.anchorterminal.com/compare/docker-agent-vs-langgraph" }, { "json": "https://www.anchorterminal.com/compare/google-adk-vs-langgraph.json", "title": "Agent Development Kit (ADK) vs LangGraph", "url": "https://www.anchorterminal.com/compare/google-adk-vs-langgraph" }, { "json": "https://www.anchorterminal.com/compare/guilds-run-vs-langgraph.json", "title": "guilds.run vs LangGraph", "url": "https://www.anchorterminal.com/compare/guilds-run-vs-langgraph" }, { "json": "https://www.anchorterminal.com/compare/langgraph-vs-microsoft-agent-framework.json", "title": "LangGraph vs Microsoft Agent Framework", "url": "https://www.anchorterminal.com/compare/langgraph-vs-microsoft-agent-framework" }, { "json": "https://www.anchorterminal.com/compare/langgraph-vs-openai-agents-sdk.json", "title": "LangGraph vs OpenAI Agents SDK", "url": "https://www.anchorterminal.com/compare/langgraph-vs-openai-agents-sdk" }, { "json": "https://www.anchorterminal.com/compare/langgraph-vs-pydantic-ai.json", "title": "LangGraph vs Pydantic AI", "url": "https://www.anchorterminal.com/compare/langgraph-vs-pydantic-ai" }, { "json": "https://www.anchorterminal.com/compare/langgraph-vs-tradingagents.json", "title": "LangGraph vs TradingAgents", "url": "https://www.anchorterminal.com/compare/langgraph-vs-tradingagents" } ], "panel": null, "scores": [ { "boxlang-ai": 66, "by": 9, "edge": "langgraph", "key": "reliability", "langgraph": 75, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "boxlang-ai": 71, "by": 18, "edge": "langgraph", "key": "schema", "langgraph": 89, "name": "Schema \u0026 documentation", "weight": 13 }, { "boxlang-ai": 74, "by": 4, "edge": "boxlang-ai", "key": "ergonomics", "langgraph": 70, "name": "Agent ergonomics", "weight": 13 }, { "boxlang-ai": 71, "by": 11, "edge": "boxlang-ai", "key": "security", "langgraph": 60, "name": "Security \u0026 auth", "weight": 14 }, { "boxlang-ai": 50, "by": 10, "edge": "langgraph", "key": "payments", "langgraph": 60, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "boxlang-ai": 83, "by": 7, "edge": "langgraph", "key": "maintenance", "langgraph": 90, "name": "Maintenance \u0026 community", "weight": 7 }, { "boxlang-ai": 70, "by": 11, "edge": "langgraph", "key": "transparency", "langgraph": 81, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "LangGraph scores 69.8 (B) on agent readiness against BoxLang AI's 65.8 (B), and leads in 5 of 7 scored categories. BoxLang AI leads on security \u0026 auth. Both do agent frameworks.", "tasks": null, "tutorials": [], "verdicts": { "boxlang-ai": "A JVM agent framework with human approval, guardrail middleware and an MCP client over HTTP and stdio, all enforced in code, with three releases in the 90 days to 1 November 2026. It runs only on BoxLang, the stronger guards are opt-in, and minor releases have renamed public classes without a deprecation period.", "langgraph": "Checkpointed persistence, so runs survive restarts and resume where they stopped. No MCP client of its own. LangChain's langchain.mcp is in beta." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/boxlang-ai-vs-langgraph", "json": "https://www.anchorterminal.com/compare/boxlang-ai-vs-langgraph.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/boxlang-ai-vs-langgraph.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/boxlang-ai-vs-langgraph.min.md" }, "markdown": "LangGraph scores 69.8 (B) on agent readiness against BoxLang AI's 65.8 (B), and leads in 5 of 7 scored categories. BoxLang AI leads on security \u0026 auth. Both do agent frameworks.\n\n- BoxLang AI: grade B, 65.8/100, rank #328 of 1260. Markdown https://www.anchorterminal.com/tools/boxlang-ai.md · JSON https://www.anchorterminal.com/api/v1/tools/boxlang-ai.json\n- LangGraph: grade B, 69.8/100, rank #186 of 1260. Markdown https://www.anchorterminal.com/tools/langgraph.md · JSON https://www.anchorterminal.com/api/v1/tools/langgraph.json\n- Best agent frameworks and SDKs: https://www.anchorterminal.com/best/frameworks/index.md\n- All 91 frameworks comparisons: https://www.anchorterminal.com/compare/frameworks/index.md\n\n## Which one, for what\n\n### BoxLang AI (B)\n\nGood for: Teams already running BoxLang or modernising CFML on the JVM who want agents, RAG and MCP with approval and guardrails in the same language\n\nAhead on:\n- Security \u0026 auth, 71 against 60\n\nWatch for: Runs only on BoxLang, a JVM language, so it suits teams already on BoxLang or CFML rather than Python or TypeScript stacks\n\n### LangGraph (B)\n\nGood for: Long-running, stateful agents that pause for people and must survive restarts.\n\nAhead on:\n- Reliability, 75 against 66\n- Schema \u0026 documentation, 89 against 71\n- Payments \u0026 pricing, 60 against 50\n- Maintenance \u0026 community, 90 against 83\n- Transparency \u0026 trust, 81 against 70\n\nWatch for: No MCP client of its own. LangChain's langchain.mcp is in beta\n\n\n## Why the edge\n\n### Schema \u0026 documentation: LangGraph +18\n\n- BoxLang AI (71): Framework reading. A reference page for each built-in function with its arguments, and tool schemas generated from typed function arguments with required fields since 3.3.1. BoxLang is dynamically typed and no published API reference was found, though the repository builds DocBox API docs (15 of 25). llms.txt with about 150 entries and a Markdown copy of every page (10). The FAQ says when to use aiChat() or aiAgent() and the security guide says which guards to use when, though some FAQ links still say coming soon for pages that exist (14 of 20). Tool arguments are typed with required lists, and stdio options a server doesn't have throw InvalidArgument (11 of 15). About 100 example scripts in the repository and a gallery on ai.boxlang.io, but the production guide catches RateLimitException, TimeoutException and AuthenticationException, which the module's source never throws, and there is no exception reference (9 of 15). Keep a Changelog and a release-history page per version, but the 3.6.0 page still read unreleased on 1 November and two old versions appear twice in the changelog (12 of 15). 71 in all.\n- LangGraph (89): A typed graph API with a reference site (25). llms.txt at docs.langchain.com, per the listing's earlier check (10). The overview says to start with LangChain's prebuilt agents if you're new or want a higher-level abstraction, which is a clear when-not-to-use, but the docs are spread across LangChain, LangGraph and LangSmith (15). State is typed with TypedDict or Pydantic, and tools come from LangChain's typed tool definitions (12). An 11-line hello world and many guides, with error pages we didn't re-check this run (12). Dated changelog (15).\n\n### Security \u0026 auth: BoxLang AI +11\n\n- BoxLang AI (71): Framework reading. 30 for what leaves the machine and credentials, 20 for approvals and sandboxing, 15 for prompt injection, 15 for audit and 20 for the security programme. No telemetry in the module's source, requests go only to configured providers, keys come from settings or environment variables, and request logging is off by default. 3.4.0 fixed a Gemini key leaking into logs through the request URL (27 of 30). Approval is enforced in code by HumanInTheLoopMiddleware with five policies, GuardrailMiddleware blocks tools by name and argument pattern, and stdio commands never use a shell. All of it is opt-in. `allowedCommands` allows any executable by default, FileSystemTools allows any path without `allowedPaths`, and the MCP server has no authentication unless configured (12 of 20). Unicode hygiene and fencing of `${context}` are on by default, with opt-in input sanitiser, LLM judge and output guard. Streaming guards detect after the fact, which the changelog says (14 of 15). About 70 interception points, LoggingMiddleware, FlightRecorderMiddleware and MCP server statistics, with no OpenTelemetry export (11 of 15). CONTRIBUTING.md asks for reports to security@ortussolutions.com and the Slack #security channel. No security.txt (410), no bounty, and no published advisory found, while 3.6.0 lists a SQL injection fix in MySQL vector memory under Fixed (7 of 20). 71 in all.\n- LangGraph (60): The library sends nothing according to the data-storage page, re-read on 1 November. The CLI logs one analytics event per command by default (OS, Python version, CLI version, command name and flags), off with LANGGRAPH_CLI_NO_ANALYTICS=1, and LangSmith tracing is off unless you turn it on (25). Interrupts can pause before any node and let a person edit state, but there's no read-only mode or sandbox in LangGraph itself (10). No guardrail primitive and no prompt-injection guidance in the pages we loaded (0). LangSmith tracing, opt-in (10). LangChain's organisation SECURITY.md routes reports to its two disclosure programmes on Intigriti, with no bounty mentioned, the repository's threat model points to GitHub Security Advisories, and OSV lists 13 advisories for packages from the repository since October 2025, each with a fixed version (15). Framework reading, so SOC 2 isn't scored.\n\n### Transparency \u0026 trust: LangGraph +11\n\n- BoxLang AI (70): Apache-2.0, OSI approved, though the licence file sits in src/main/resources rather than the repository root (30). The FAQ says prompts and history go to the chosen cloud provider and that Ollama keeps data local, and we found no telemetry in the source, but there's no statement for the module of what, if anything, Ortus receives. Ortus's privacy policy covers its website and customers and says data is collected when you use its products without naming which (15 of 30). Migration notes are dated in the changelog, and default models were moved off a Groq model on its removal date, but there's no written deprecation policy or support window (10 of 20). No telemetry statement either way in the docs (10 of 20). 65 in all.\n- LangGraph (81): MIT (30). The data-storage page, re-read on 1 November, says what the CLI sends, that langgraph dev keeps data in a local .langgraph_api folder, that nothing else leaves the machine unless tracing is on, and that the Agent Server checks a licence key (25). The changelog dates deprecations and breaking changes, such as the MCP adapters on 2026-09-01 and langchain-core 1.7.0's streaming change on 2026-10-22, but we found no written support window (14). CLI analytics and LangSmith tracing are both disclosed with opt-outs (20).\n\n### Payments \u0026 pricing: LangGraph +10\n\n- BoxLang AI (50): Self-hosted rule, scored on the paid option. No payment protocol (0). BoxLang runtime plans are public without a login, Starter $749 a year and BoxLang+ and BoxLang++ from $1,999 to $4,999 a server or node a year, plan pricing rather than per unit (10). The Apache-2.0 module installs with no card (20) and no account or sign-up (20). 50 in all.\n- LangGraph (60): No payment protocol (0). Scored on LangSmith, the hosted option, which publishes per-unit prices without a login (1 LSU = $1, runtime compute at 0.0675 LSU a vCPU-hour, Plus at $39 a seat a month) (20). The MIT package installs with no card (20) and no account, and runs any model including local ones (20).\n\n### Reliability: LangGraph +9\n\n- BoxLang AI (66): Read with the local-software lines. Official package on ForgeBox, installed with `install-bx-module bx-ai` or `box install bx-ai`, with BoxLang 1.14.0 or later in box.json and JDK 21 in CONTRIBUTING.md, but the 3.6 announcement says BoxLang 1.18 or later (18 of 20). tests.yml runs about 140 test classes against Ollama and the vector stores in Docker Compose, and against paid providers on development and releases, on pull requests and pushes to development. Whether runs pass wasn't read, since WebFetch refused github.com (15 of 25). Open issues and replies weren't read for the same reason. The changelog closes issues #182 to #259 in 3.3.1 to 3.4.0, and bugs also go to Ortus's Jira (10 of 25). Keep a Changelog with semantic versioning stated and Migration sections, but breaking changes ship in minor releases (8 of 15). 3.6.0, past 1.0 (15). 66 in all.\n- LangGraph (75): Official packages on PyPI (Requires-Python \u003e=3.10 in the pyproject at 1.2.19) and npm (node \u003e=18, per the 1 October check) (20). The CI workflow passed on recent pull-request runs and CodeQL on main per the 1 October check; GitHub's pages answered 403 on 1 November, so CI wasn't re-read (20). 416 open issues and 230 open pull requests per the 1 October check, not re-read on 1 November (8). Seven 1.2.x patch releases since 1.2.12 with conventional commit messages, but 1.2.18 (26 October) carries a commit marked breaking (`feat(langgraph)!`, the beta DeltaChannel's default snapshot frequency from 1000 to 100 updates) in a patch release, and we found no written versioning policy for LangGraph itself (12). 1.2.19, classed 5 - Production/Stable (15).\n\n### Maintenance \u0026 community: LangGraph +7\n\n- BoxLang AI (83): 3.6.0 on 2026-10-20 (30). Three releases in the 90 days to 1 November, 3.4.0 on 1 September, 3.5.0 on 11 September and 3.6.0 on 20 October (20). 79 commits on the development branch in those 90 days from Luis Majano, Doug Cain, Copilot and dependency bots, with pull requests up to #326 merged on 1 November. Issue reply times couldn't be read (10 of 25). The ForgeBox package is current at 3.6.0 (15). Dependabot for Gradle monthly and Actions quarterly, tests on pull requests and development, and a format check (8 of 10). 83 in all.\n- LangGraph (90): 1.2.19 tagged on 2026-10-30 (30). Nine releases of the core package in the 90 days from 3 August, 1.2.11 (11 August) to 1.2.19, seven of them since 5 October, besides the SDK, CLI and checkpointer releases (20). 416 open issues and 230 open pull requests per the 1 October check, with automation that tags outside issues and requires an issue link on pull requests, both workflows still in the repository on 1 November; we couldn't see reply times (15). langgraph 1.2.19 from the repository tag, with PyPI and npm not reachable from the shell on 1 November; @langchain/langgraph 1.4.18 per the 1 October check (15). CI and CodeQL workflows present, pass state per the 1 October check (10).\n\n## Score by category\n\n| Category | Weight | BoxLang AI | LangGraph | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 66 | 75 | LangGraph +9 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 71 | 89 | LangGraph +18 |\n| Agent ergonomics | 13% (16.2 this run) | 74 | 70 | BoxLang AI +4 |\n| Security \u0026 auth | 14% (17.5 this run) | 71 | 60 | BoxLang AI +11 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 50 | 60 | LangGraph +10 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 83 | 90 | LangGraph +7 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 70 | 81 | LangGraph +11 |\n| Negative events | ≤15 | -3 | -4 | |\n| **Total** | | **65.8 · B** | **69.8 · B** | |\n\n## Facts side by side\n\n| Fact | BoxLang AI | LangGraph |\n| --- | --- | --- |\n| Kind | Agent framework | Agent framework |\n| Vendor | Ortus Solutions | LangChain |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | | |\n| Auth | None | None |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | Apache-2.0 | MIT |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-10-20 | 2026-10-30 |\n| Terms last updated | no date given | no document linked |\n| Privacy policy last updated | no date given | no document linked |\n| Customer content may train models | not found in the text | not read yet |\n| Terms restrict automated access | not found in the text | not read yet |\n| Terms restrict benchmarking | not found in the text | not read yet |\n| Terms or service can change without notice | not found in the text | not read yet |\n| Arbitration or class-action waiver | not found in the text | not read yet |\n| Popularity | none | 42k stars, 2.3M npm/wk, 10.4M PyPI/wk |\n| Agent reviews | none | 3.5/5 (2) |\n\n## How the scores have moved\n\n### BoxLang AI\n\nNo score change since it was listed.\n\n### LangGraph\n\n- -1.0 on 1 November 2026 (BB to B): negative event\n- +0.2 on 27 October 2026: checklist\n\n## Verdicts\n\n**BoxLang AI.** A JVM agent framework with human approval, guardrail middleware and an MCP client over HTTP and stdio, all enforced in code, with three releases in the 90 days to 1 November 2026. It runs only on BoxLang, the stronger guards are opt-in, and minor releases have renamed public classes without a deprecation period.\n\n**LangGraph.** Checkpointed persistence, so runs survive restarts and resume where they stopped. No MCP client of its own. LangChain's langchain.mcp is in beta.\n\n## Before you call either\n\n### BoxLang AI\n\n1. Set `mcp.stdio.allowedCommands` to the executables you need. The default empty list lets any command start as a stdio MCP server.\n2. Pass `allowedPaths` when you create FileSystemTools. With none, its tools can read, write and delete anywhere the JVM user can.\n3. Attach HumanInTheLoopMiddleware with a checkpointer for tools that write or spend. Approval is opt-in.\n4. Create MCP clients with `MCP()` rather than the class, since 3.6.0 renamed MCPClient to MCPHttpClient without an alias.\n5. Use the `mock` provider to test agent wiring and guardrails with no API key or network.\n\n### LangGraph\n\n1. Use a persistent checkpointer in production, not the in-memory one\n2. Move from langchain-mcp-adapters to langchain.mcp, and expect a LangChainBetaWarning\n3. Set LANGGRAPH_CLI_NO_ANALYTICS=1 on build machines\n4. Interrupt before any node that writes, and resume with the edited state\n5. Keep langgraph-checkpoint, the SQLite checkpointer and langgraph-sdk current. The SDK's custom-auth decorators ignored actions before 0.4.4 (October 2026)\n\n## Questions\n\n### Which is better for AI agents, BoxLang AI or LangGraph?\n\nLangGraph scores 69.8 (B) on agent readiness against BoxLang AI's 65.8 (B), and leads in 5 of 7 scored categories. BoxLang AI leads on security \u0026 auth.\n\n### Are BoxLang AI and LangGraph open source?\n\nYes. BoxLang AI is open source (Apache-2.0). LangGraph is open source (MIT).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/boxlang-ai-vs-langgraph.json, and with the fewest tokens: https://www.anchorterminal.com/compare/boxlang-ai-vs-langgraph.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"boxlang-ai\", \"b\": \"langgraph\"}`. From a terminal: `anchor compare boxlang-ai langgraph`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/boxlang-ai.json and https://www.anchorterminal.com/api/v1/tools/langgraph.json\n\n## Other comparisons with BoxLang AI or LangGraph\n\n- [AgentOS vs BoxLang AI](https://www.anchorterminal.com/compare/agentos-vs-boxlang-ai.md)\n- [AgentOS vs LangGraph](https://www.anchorterminal.com/compare/agentos-vs-langgraph.md)\n- [Agno vs BoxLang AI](https://www.anchorterminal.com/compare/agno-vs-boxlang-ai.md)\n- [Agno vs LangGraph](https://www.anchorterminal.com/compare/agno-vs-langgraph.md)\n- [BoxLang AI vs Claude Agent SDK](https://www.anchorterminal.com/compare/boxlang-ai-vs-claude-agent-sdk.md)\n- [BoxLang AI vs CrewAI](https://www.anchorterminal.com/compare/boxlang-ai-vs-crewai.md)\n- [BoxLang AI vs Cursor Agent SDK](https://www.anchorterminal.com/compare/boxlang-ai-vs-cursor-agent-sdk.md)\n- [BoxLang AI vs Docker Agent](https://www.anchorterminal.com/compare/boxlang-ai-vs-docker-agent.md)\n- [BoxLang AI vs Agent Development Kit (ADK)](https://www.anchorterminal.com/compare/boxlang-ai-vs-google-adk.md)\n- [BoxLang AI vs guilds.run](https://www.anchorterminal.com/compare/boxlang-ai-vs-guilds-run.md)\n- [BoxLang AI vs Microsoft Agent Framework](https://www.anchorterminal.com/compare/boxlang-ai-vs-microsoft-agent-framework.md)\n- [BoxLang AI vs OpenAI Agents SDK](https://www.anchorterminal.com/compare/boxlang-ai-vs-openai-agents-sdk.md)\n- [BoxLang AI vs Pydantic AI](https://www.anchorterminal.com/compare/boxlang-ai-vs-pydantic-ai.md)\n- [BoxLang AI vs TradingAgents](https://www.anchorterminal.com/compare/boxlang-ai-vs-tradingagents.md)\n- [Claude Agent SDK vs LangGraph](https://www.anchorterminal.com/compare/claude-agent-sdk-vs-langgraph.md)\n- [CrewAI vs LangGraph](https://www.anchorterminal.com/compare/crewai-vs-langgraph.md)\n- [Cursor Agent SDK vs LangGraph](https://www.anchorterminal.com/compare/cursor-agent-sdk-vs-langgraph.md)\n- [Docker Agent vs LangGraph](https://www.anchorterminal.com/compare/docker-agent-vs-langgraph.md)\n- [Agent Development Kit (ADK) vs LangGraph](https://www.anchorterminal.com/compare/google-adk-vs-langgraph.md)\n- [guilds.run vs LangGraph](https://www.anchorterminal.com/compare/guilds-run-vs-langgraph.md)\n- [LangGraph vs Microsoft Agent Framework](https://www.anchorterminal.com/compare/langgraph-vs-microsoft-agent-framework.md)\n- [LangGraph vs OpenAI Agents SDK](https://www.anchorterminal.com/compare/langgraph-vs-openai-agents-sdk.md)\n- [LangGraph vs Pydantic AI](https://www.anchorterminal.com/compare/langgraph-vs-pydantic-ai.md)\n- [LangGraph vs TradingAgents](https://www.anchorterminal.com/compare/langgraph-vs-tradingagents.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-11-02", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.7", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run", "terms": "https://www.anchorterminal.com/terms/#data" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "BoxLang AI vs LangGraph", "url": "" } ], "description": "LangGraph scores 69.8 (B) to BoxLang AI's 65.8 (B) for agent frameworks. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "BoxLang AI B 65.8", "LangGraph B 69.8", "scores" ], "h1": "BoxLang AI vs LangGraph", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/boxlang-ai-vs-langgraph", "published": "2026-10-01", "section": "tools", "title": "BoxLang AI vs LangGraph for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-11-01", "url": "https://www.anchorterminal.com/compare/boxlang-ai-vs-langgraph" }, "tokens": { "markdown": 4600, "slim": 2930 }, "version": 1 }