{ "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": 403, "ranked": true, "rankOf": 1510, "categoryRank": 14, "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", "live": { "slug": "boxlang-ai", "versions": [ { "registry": "github", "name": "ortus-boxlang/bx-ai", "version": "v3.7.0", "released": "2026-11-04", "seenAt": "2026-11-06T23:11:59.483535804Z" } ], "githubStars": 20, "securityTxt": { "url": "https://ortussolutions.com/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-07T15:59:35.513461646Z" }, "llmsTxt": { "url": "https://ai.ortusbooks.com/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:31:44.174922688Z" }, "pages": [ { "url": "https://raw.githubusercontent.com/ortus-boxlang/bx-ai/main/changelog.md", "kind": "changelog", "status": 304, "checkedAt": "2026-11-07T14:22:35.612698873Z", "changedAt": "2026-11-04T08:34:53.336221384Z", "fingerprint": "f8be668a6e44" }, { "url": "https://www.ortussolutions.com/about-us/ortus-privacy-policy", "kind": "privacy", "status": 200, "checkedAt": "2026-11-07T14:32:35.59600414Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "b4280b39a3d6" }, { "url": "https://raw.githubusercontent.com/ortus-boxlang/bx-ai/main/src/main/resources/LICENSE", "kind": "terms", "status": 304, "checkedAt": "2026-11-07T14:22:37.201712876Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "839fbbcddc72" } ], "github": { "repo": "ortus-boxlang/bx-ai", "checkedAt": "2026-11-02T08:22:41.470134886Z", "stars": 19, "archived": false, "issuesEnabled": true, "pushedAt": "2026-11-01T17:24:53Z", "openIssues": 10, "openPRs": 8, "issuesOpened90d": 9, "issuesClosed90d": 9, "prsMerged90d": 65, "ci": { "branch": "development", "runs": 50, "success": 9, "failure": 28, "other": 13, "latest": "failure", "latestAt": "2026-11-01T17:37:12Z" }, "replies": { "sampled": 25, "unanswered": 7, "medianDays": 0.8 } }, "updatedAt": "2026-11-07T15:59:35.513461646Z" } }, "answer": "LlamaIndex Framework scores 70 (BB) on agent readiness against BoxLang AI's 65.8 (B), and leads in 4 of 7 scored categories. BoxLang AI leads on maintenance \u0026 community.", "b": { "slug": "llamaindex", "name": "LlamaIndex Framework", "vendor": "LlamaIndex", "vendorUrl": "https://developers.llamaindex.ai/python/framework/", "kind": "framework", "category": "frameworks", "summary": "The LlamaIndex Framework is LlamaIndex's open-source Python toolkit for retrieval and agents, with FunctionAgent, ReActAgent and CodeActAgent, multi-agent AgentWorkflow, event-driven Workflows, MCP tools and hundreds of integration packages.", "url": "https://www.anchorterminal.com/tools/llamaindex", "markdownUrl": "https://www.anchorterminal.com/tools/llamaindex.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/llamaindex.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/llamaindex.json", "dns": "llamaindex.grade.anchorterminal.com", "repo": "https://github.com/run-llama/llama_index", "license": "MIT", "transports": [], "packages": [ { "registry": "pypi", "name": "llama-index" }, { "registry": "pypi", "name": "llama-index-core" }, { "registry": "pypi", "name": "llama-index-workflows" }, { "registry": "pypi", "name": "llama-index-tools-mcp" } ], "auth": "none", "authNotes": "A library with no credentials of its own. The default LLM and embeddings are OpenAI's and read an OpenAI key; integrations take their own keys.", "pricing": "free", "pricingNotes": "Free and open source under MIT. You pay for model calls. LlamaParse and LlamaCloud are separate paid services with their own Anchor Terminal listing.", "priceSummary": "Free · OSS", "where": "library", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the framework docs or the repository (checked 2026-11-06).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 52833, "npmWeekly": null, "pypiWeekly": 1260039, "asOf": "2026-11-06" }, "docsUrl": "https://developers.llamaindex.ai/python/framework/", "llmsTxt": "https://developers.llamaindex.ai/llms.txt", "capabilities": [ "agent.framework", "agent.multi-agent", "agent.durable", "agent.mcp-client" ], "tags": [ "framework", "python", "open-source", "llms-txt", "mcp", "rag", "workflows" ], "lastRelease": "2026-09-21", "graded": true, "anchor": { "graded": true, "score": 70, "grade": "BB", "agentReady": true, "rank": 217, "ranked": true, "rankOf": 1510, "categoryRank": 11, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 73, "maintenance": 69, "payments": 60, "reliability": 70, "schema": 85, "security": 74, "transparency": 67 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-06" }, "negative": -2, "negativeNotes": [ "2025-11 to 2026-11. Advisories for llama-index-core first published in the last 12 months are GHSA-488g-hw5f-x29p (uncontrolled resource consumption, 2 February 2026, moderate, fixed in 0.12.41) and the PYSEC re-publications in 2026 of 2025 path-traversal, denial-of-service and temporary-file issues fixed by 0.13.0. Fixed and documented, so 2 points. https://osv.dev/vulnerability/GHSA-488g-hw5f-x29p" ], "verdict": "An MIT Python framework for retrieval and agents, with three agent types, multi-agent AgentWorkflow, resumable event-driven Workflows, MCP tools and a huntr bug bounty, and no telemetry found. Core is still 0.14 with breaking minors, OpenAI is the silent default, and approval and injection handling are left to the application.", "bestFor": "Python teams building retrieval-heavy agents over their own data, with many connectors.", "strengths": [ "FunctionAgent, ReActAgent, CodeActAgent and multi-agent AgentWorkflow over one Workflows engine", "Workflow context serialises and resumes, with a DBOS package for durable runs", "Hundreds of integration packages for models, vector stores and data loaders", "No telemetry found in llama-index-core", "huntr bug bounty and public advisories with fixed versions" ], "weaknesses": [ "Core is 0.14.x, and minor versions such as 0.13 and 0.14 carried breaking changes", "OpenAI is the default LLM and embedding provider unless Settings is changed", "No per-tool approval primitive; the threat model leaves input validation to the application", "Several 2025 path-traversal and denial-of-service advisories in core and readers" ], "agentNotes": [ "Set Settings.llm and Settings.embed_model explicitly so calls don't go to OpenAI by default", "Install llama-index-tools-mcp for MCP tools and pass only the allowed tools the task needs", "Use Workflow human-in-the-loop events before tools that write or send", "Pin llama-index-core to a minor version, since minors have broken APIs", "Upgrade llama-index-core to 0.13.0 or later to clear the 2025 advisories" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "BB", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 70 } ], "editorialScores": { "ergonomics": 73, "maintenance": 69, "payments": 60, "reliability": 70, "schema": 85, "security": 74, "transparency": 72 }, "provenanceScore": 61, "checked": { "categories": { "ergonomics": "2026-11-06", "maintenance": "2026-11-06", "payments": "2026-11-06", "reliability": "2026-11-06", "schema": "2026-11-06", "security": "2026-11-06", "transparency": "2026-11-06" }, "last": "2026-11-06", "oldest": "2026-11-06", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install llama-index # MCP tools: pip install llama-index-tools-mcp" }, "letme": { "capability": "https://letme.dev/agent.framework", "tool": "https://letme.dev/llamaindex" }, "sameCompany": [ "llamaparse" ], "area": "frameworks", "provenance": { "legalEntity": "LlamaIndex, Inc.", "domain": "llamaindex.ai", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "", "privacy": "https://www.llamaindex.ai/privacy-policy", "statusPage": "", "changelog": "https://github.com/run-llama/llama_index/blob/main/CHANGELOG.md", "securityTxt": "unknown", "checked": "2026-11-06", "notes": [ "The framework is MIT-licensed; the company facts follow the LlamaParse listing.", "developers.llamaindex.ai/robots.txt allows all crawlers.", "The privacy policy link is the company's; the library collects nothing itself. Neither the terms nor the privacy policy was re-read for this listing." ], "score": 61 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/llamaindex.json", "live": { "slug": "llamaindex", "versions": [ { "registry": "github", "name": "run-llama/llama_index", "version": "v0.14.25", "released": "2026-09-21", "seenAt": "2026-11-06T23:41:01.613169751Z" }, { "registry": "pypi", "name": "llama-index", "version": "0.14.25", "released": "2026-09-21", "seenAt": "2026-11-06T23:40:55.516520624Z" }, { "registry": "pypi", "name": "llama-index-core", "version": "0.14.25", "released": "2026-09-21", "seenAt": "2026-11-06T23:40:55.720658841Z" }, { "registry": "pypi", "name": "llama-index-tools-mcp", "version": "0.6.0", "released": "2026-08-31", "seenAt": "2026-11-06T23:41:00.102033357Z" }, { "registry": "pypi", "name": "llama-index-workflows", "version": "2.26.1", "released": "2026-10-21", "seenAt": "2026-11-06T23:40:57.534551463Z" } ], "githubStars": 52835, "pypiWeekly": 409969, "securityTxt": { "url": "https://llamaindex.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-07T16:01:24.67649536Z" }, "llmsTxt": { "url": "https://developers.llamaindex.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:32:53.290758373Z" }, "pages": [ { "url": "https://raw.githubusercontent.com/run-llama/llama_index/main/CHANGELOG.md", "kind": "changelog", "status": 200, "checkedAt": "2026-11-07T14:23:19.050779794Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "51de27bb70e4" }, { "url": "https://www.llamaindex.ai/privacy-policy", "kind": "privacy", "status": 200, "checkedAt": "2026-11-07T14:30:58.312656283Z", "changedAt": "2026-11-06T13:51:36.031111139Z", "fingerprint": "22f247245013" } ], "updatedAt": "2026-11-07T16:01:24.67649536Z" } }, "edges": [ { "by": 14, "category": "schema", "leads": "llamaindex", "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": "Framework reading. A typed Python API with a generated reference (22). llms.txt indexing the framework docs, plus a docs search API and an MCP server for the docs (10). The agents guide says what each agent class is for, and the MCP page lists the three ways to use MCP (15). Tools are typed from function signatures and Pydantic models (13). Many examples and notebooks, few documented error types (10). Dated changelog (15). 22+10+15+13+10+15 = 85." }, "scores": { "a": 71, "b": 85 } }, { "by": 14, "category": "maintenance", "leads": "boxlang-ai", "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": "llama-index-core 0.14.25 on 21 September 2026, 46 days before this check (20). Two core changelog entries in the 90 days (19 August and 21 September), with integration packages and Workflows (2.24.1 to 2.26.1) publishing in between, so partial (12). 379 open issues and 1,291 open issues and pull requests on 6 November, with 241 issues opened in the 90 days to 3 November. Of the 50 newest, 28 had a comment and 3 were closed; a stale bot and an issue classifier run on the repository (12). Core, Workflows and integrations are current (15). CI and CodeQL passing on main and a stale-package policy that moves unmaintained integrations out of main (10). 20+12+12+15+10 = 69." }, "scores": { "a": 83, "b": 69 } }, { "by": 10, "category": "payments", "leads": "llamaindex", "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": "Self-hosted rule. Free MIT packages with nothing to buy for the framework itself (20 + 20 + 20). No payment protocol (0). LlamaCloud is graded on its own listing. 0+20+20+20 = 60." }, "scores": { "a": 50, "b": 60 } } ], "facts": [ { "a": "Agent framework", "b": "Agent framework", "name": "Kind" }, { "a": "Ortus Solutions", "b": "LlamaIndex", "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": "2026-09-21", "name": "Last release" }, { "a": "no date given", "b": "no document linked", "name": "Terms last updated" }, { "a": "no date given", "b": "2026-08-24", "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": "53k stars, 1.3M PyPI/wk", "name": "Popularity" } ], "faq": [ { "answer": "LlamaIndex Framework scores 70 (BB) on agent readiness against BoxLang AI's 65.8 (B), and leads in 4 of 7 scored categories. BoxLang AI leads on maintenance \u0026 community.", "question": "Which is better for AI agents, BoxLang AI or LlamaIndex Framework?" }, { "answer": "Yes. BoxLang AI is open source (Apache-2.0). LlamaIndex Framework is open source (MIT).", "question": "Are BoxLang AI and LlamaIndex Framework open source?" } ], "goodFor": [ { "aheadOn": [ "Maintenance \u0026 community, 83 against 69" ], "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": [ "Schema \u0026 documentation, 85 against 71", "Payments \u0026 pricing, 60 against 50" ], "also": [ "Agent-ready, a grade of BB or better" ], "goodFor": "Python teams building retrieval-heavy agents over their own data, with many connectors.", "slug": "llamaindex", "watchFor": "Core is 0.14.x, and minor versions such as 0.13 and 0.14 carried breaking changes" } ], "history": null, "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-llamaindex.json", "title": "AgentOS vs LlamaIndex Framework", "url": "https://www.anchorterminal.com/compare/agentos-vs-llamaindex" }, { "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-llamaindex.json", "title": "Agno vs LlamaIndex Framework", "url": "https://www.anchorterminal.com/compare/agno-vs-llamaindex" }, { "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-langgraph.json", "title": "BoxLang AI vs LangGraph", "url": "https://www.anchorterminal.com/compare/boxlang-ai-vs-langgraph" }, { "json": "https://www.anchorterminal.com/compare/boxlang-ai-vs-mastra.json", "title": "BoxLang AI vs Mastra", "url": "https://www.anchorterminal.com/compare/boxlang-ai-vs-mastra" }, { "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-smolagents.json", "title": "BoxLang AI vs smolagents", "url": "https://www.anchorterminal.com/compare/boxlang-ai-vs-smolagents" }, { "json": "https://www.anchorterminal.com/compare/boxlang-ai-vs-strands-agents.json", "title": "BoxLang AI vs Strands Agents", "url": "https://www.anchorterminal.com/compare/boxlang-ai-vs-strands-agents" }, { "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/boxlang-ai-vs-vercel-ai-sdk.json", "title": "BoxLang AI vs AI SDK", "url": "https://www.anchorterminal.com/compare/boxlang-ai-vs-vercel-ai-sdk" }, { "json": "https://www.anchorterminal.com/compare/claude-agent-sdk-vs-llamaindex.json", "title": "Claude Agent SDK vs LlamaIndex Framework", "url": "https://www.anchorterminal.com/compare/claude-agent-sdk-vs-llamaindex" }, { "json": "https://www.anchorterminal.com/compare/crewai-vs-llamaindex.json", "title": "CrewAI vs LlamaIndex Framework", "url": "https://www.anchorterminal.com/compare/crewai-vs-llamaindex" }, { "json": "https://www.anchorterminal.com/compare/cursor-agent-sdk-vs-llamaindex.json", "title": "Cursor Agent SDK vs LlamaIndex Framework", "url": "https://www.anchorterminal.com/compare/cursor-agent-sdk-vs-llamaindex" }, { "json": "https://www.anchorterminal.com/compare/docker-agent-vs-llamaindex.json", "title": "Docker Agent vs LlamaIndex Framework", "url": "https://www.anchorterminal.com/compare/docker-agent-vs-llamaindex" }, { "json": "https://www.anchorterminal.com/compare/google-adk-vs-llamaindex.json", "title": "Agent Development Kit (ADK) vs LlamaIndex Framework", "url": "https://www.anchorterminal.com/compare/google-adk-vs-llamaindex" }, { "json": "https://www.anchorterminal.com/compare/guilds-run-vs-llamaindex.json", "title": "guilds.run vs LlamaIndex Framework", "url": "https://www.anchorterminal.com/compare/guilds-run-vs-llamaindex" }, { "json": "https://www.anchorterminal.com/compare/langgraph-vs-llamaindex.json", "title": "LangGraph vs LlamaIndex Framework", "url": "https://www.anchorterminal.com/compare/langgraph-vs-llamaindex" }, { "json": "https://www.anchorterminal.com/compare/llamaindex-vs-mastra.json", "title": "LlamaIndex Framework vs Mastra", "url": "https://www.anchorterminal.com/compare/llamaindex-vs-mastra" }, { "json": "https://www.anchorterminal.com/compare/llamaindex-vs-microsoft-agent-framework.json", "title": "LlamaIndex Framework vs Microsoft Agent Framework", "url": "https://www.anchorterminal.com/compare/llamaindex-vs-microsoft-agent-framework" }, { "json": "https://www.anchorterminal.com/compare/llamaindex-vs-openai-agents-sdk.json", "title": "LlamaIndex Framework vs OpenAI Agents SDK", "url": "https://www.anchorterminal.com/compare/llamaindex-vs-openai-agents-sdk" }, { "json": "https://www.anchorterminal.com/compare/llamaindex-vs-pydantic-ai.json", "title": "LlamaIndex Framework vs Pydantic AI", "url": "https://www.anchorterminal.com/compare/llamaindex-vs-pydantic-ai" }, { "json": "https://www.anchorterminal.com/compare/llamaindex-vs-smolagents.json", "title": "LlamaIndex Framework vs smolagents", "url": "https://www.anchorterminal.com/compare/llamaindex-vs-smolagents" }, { "json": "https://www.anchorterminal.com/compare/llamaindex-vs-strands-agents.json", "title": "LlamaIndex Framework vs Strands Agents", "url": "https://www.anchorterminal.com/compare/llamaindex-vs-strands-agents" }, { "json": "https://www.anchorterminal.com/compare/llamaindex-vs-tradingagents.json", "title": "LlamaIndex Framework vs TradingAgents", "url": "https://www.anchorterminal.com/compare/llamaindex-vs-tradingagents" }, { "json": "https://www.anchorterminal.com/compare/llamaindex-vs-vercel-ai-sdk.json", "title": "LlamaIndex Framework vs AI SDK", "url": "https://www.anchorterminal.com/compare/llamaindex-vs-vercel-ai-sdk" } ], "panel": null, "scores": [ { "boxlang-ai": 66, "by": 4, "edge": "llamaindex", "key": "reliability", "llamaindex": 70, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "boxlang-ai": 71, "by": 14, "edge": "llamaindex", "key": "schema", "llamaindex": 85, "name": "Schema \u0026 documentation", "weight": 13 }, { "boxlang-ai": 74, "by": 1, "edge": "boxlang-ai", "key": "ergonomics", "llamaindex": 73, "name": "Agent ergonomics", "weight": 13 }, { "boxlang-ai": 71, "by": 3, "edge": "llamaindex", "key": "security", "llamaindex": 74, "name": "Security \u0026 auth", "weight": 14 }, { "boxlang-ai": 50, "by": 10, "edge": "llamaindex", "key": "payments", "llamaindex": 60, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "boxlang-ai": 83, "by": 14, "edge": "boxlang-ai", "key": "maintenance", "llamaindex": 69, "name": "Maintenance \u0026 community", "weight": 7 }, { "boxlang-ai": 70, "by": 3, "edge": "boxlang-ai", "key": "transparency", "llamaindex": 67, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "LlamaIndex Framework scores 70 (BB) on agent readiness against BoxLang AI's 65.8 (B), and leads in 4 of 7 scored categories. BoxLang AI leads on maintenance \u0026 community. 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.", "llamaindex": "An MIT Python framework for retrieval and agents, with three agent types, multi-agent AgentWorkflow, resumable event-driven Workflows, MCP tools and a huntr bug bounty, and no telemetry found. Core is still 0.14 with breaking minors, OpenAI is the silent default, and approval and injection handling are left to the application." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/boxlang-ai-vs-llamaindex", "json": "https://www.anchorterminal.com/compare/boxlang-ai-vs-llamaindex.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/boxlang-ai-vs-llamaindex.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/boxlang-ai-vs-llamaindex.min.md" }, "markdown": "LlamaIndex Framework scores 70 (BB) on agent readiness against BoxLang AI's 65.8 (B), and leads in 4 of 7 scored categories. BoxLang AI leads on maintenance \u0026 community. Both do agent frameworks.\n\n- BoxLang AI: grade B, 65.8/100, rank #403 of 1510. Markdown https://www.anchorterminal.com/tools/boxlang-ai.md · JSON https://www.anchorterminal.com/api/v1/tools/boxlang-ai.json\n- LlamaIndex Framework: grade BB, 70/100, rank #217 of 1510. Markdown https://www.anchorterminal.com/tools/llamaindex.md · JSON https://www.anchorterminal.com/api/v1/tools/llamaindex.json\n- Best agent frameworks and SDKs: https://www.anchorterminal.com/best/frameworks/index.md\n- All 171 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- Maintenance \u0026 community, 83 against 69\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### LlamaIndex Framework (BB)\n\nGood for: Python teams building retrieval-heavy agents over their own data, with many connectors.\n\nAhead on:\n- Schema \u0026 documentation, 85 against 71\n- Payments \u0026 pricing, 60 against 50\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n\nWatch for: Core is 0.14.x, and minor versions such as 0.13 and 0.14 carried breaking changes\n\n\n## Why the edge\n\n### Schema \u0026 documentation: LlamaIndex Framework +14\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- LlamaIndex Framework (85): Framework reading. A typed Python API with a generated reference (22). llms.txt indexing the framework docs, plus a docs search API and an MCP server for the docs (10). The agents guide says what each agent class is for, and the MCP page lists the three ways to use MCP (15). Tools are typed from function signatures and Pydantic models (13). Many examples and notebooks, few documented error types (10). Dated changelog (15). 22+10+15+13+10+15 = 85.\n\n### Maintenance \u0026 community: BoxLang AI +14\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- LlamaIndex Framework (69): llama-index-core 0.14.25 on 21 September 2026, 46 days before this check (20). Two core changelog entries in the 90 days (19 August and 21 September), with integration packages and Workflows (2.24.1 to 2.26.1) publishing in between, so partial (12). 379 open issues and 1,291 open issues and pull requests on 6 November, with 241 issues opened in the 90 days to 3 November. Of the 50 newest, 28 had a comment and 3 were closed; a stale bot and an issue classifier run on the repository (12). Core, Workflows and integrations are current (15). CI and CodeQL passing on main and a stale-package policy that moves unmaintained integrations out of main (10). 20+12+12+15+10 = 69.\n\n### Payments \u0026 pricing: LlamaIndex Framework +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- LlamaIndex Framework (60): Self-hosted rule. Free MIT packages with nothing to buy for the framework itself (20 + 20 + 20). No payment protocol (0). LlamaCloud is graded on its own listing. 0+20+20+20 = 60.\n\n## Score by category\n\n| Category | Weight | BoxLang AI | LlamaIndex Framework | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 66 | 70 | LlamaIndex Framework +4 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 71 | 85 | LlamaIndex Framework +14 |\n| Agent ergonomics | 13% (16.2 this run) | 74 | 73 | BoxLang AI +1 |\n| Security \u0026 auth | 14% (17.5 this run) | 71 | 74 | LlamaIndex Framework +3 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 50 | 60 | LlamaIndex Framework +10 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 83 | 69 | BoxLang AI +14 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 70 | 67 | BoxLang AI +3 |\n| Negative events | ≤15 | -3 | -2 | |\n| **Total** | | **65.8 · B** | **70 · BB** | |\n\n## Facts side by side\n\n| Fact | BoxLang AI | LlamaIndex Framework |\n| --- | --- | --- |\n| Kind | Agent framework | Agent framework |\n| Vendor | Ortus Solutions | LlamaIndex |\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 | 2026-09-21 |\n| Terms last updated | no date given | no document linked |\n| Privacy policy last updated | no date given | 2026-08-24 |\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 | 53k stars, 1.3M PyPI/wk |\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**LlamaIndex Framework.** An MIT Python framework for retrieval and agents, with three agent types, multi-agent AgentWorkflow, resumable event-driven Workflows, MCP tools and a huntr bug bounty, and no telemetry found. Core is still 0.14 with breaking minors, OpenAI is the silent default, and approval and injection handling are left to the application.\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### LlamaIndex Framework\n\n1. Set Settings.llm and Settings.embed_model explicitly so calls don't go to OpenAI by default\n2. Install llama-index-tools-mcp for MCP tools and pass only the allowed tools the task needs\n3. Use Workflow human-in-the-loop events before tools that write or send\n4. Pin llama-index-core to a minor version, since minors have broken APIs\n5. Upgrade llama-index-core to 0.13.0 or later to clear the 2025 advisories\n\n## Questions\n\n### Which is better for AI agents, BoxLang AI or LlamaIndex Framework?\n\nLlamaIndex Framework scores 70 (BB) on agent readiness against BoxLang AI's 65.8 (B), and leads in 4 of 7 scored categories. BoxLang AI leads on maintenance \u0026 community.\n\n### Are BoxLang AI and LlamaIndex Framework open source?\n\nYes. BoxLang AI is open source (Apache-2.0). LlamaIndex Framework is open source (MIT).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/boxlang-ai-vs-llamaindex.json, and with the fewest tokens: https://www.anchorterminal.com/compare/boxlang-ai-vs-llamaindex.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"boxlang-ai\", \"b\": \"llamaindex\"}`. From a terminal: `anchor compare boxlang-ai llamaindex`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/boxlang-ai.json and https://www.anchorterminal.com/api/v1/tools/llamaindex.json\n\n## Other comparisons with BoxLang AI or LlamaIndex Framework\n\n- [AgentOS vs BoxLang AI](https://www.anchorterminal.com/compare/agentos-vs-boxlang-ai.md)\n- [AgentOS vs LlamaIndex Framework](https://www.anchorterminal.com/compare/agentos-vs-llamaindex.md)\n- [Agno vs BoxLang AI](https://www.anchorterminal.com/compare/agno-vs-boxlang-ai.md)\n- [Agno vs LlamaIndex Framework](https://www.anchorterminal.com/compare/agno-vs-llamaindex.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 LangGraph](https://www.anchorterminal.com/compare/boxlang-ai-vs-langgraph.md)\n- [BoxLang AI vs Mastra](https://www.anchorterminal.com/compare/boxlang-ai-vs-mastra.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 smolagents](https://www.anchorterminal.com/compare/boxlang-ai-vs-smolagents.md)\n- [BoxLang AI vs Strands Agents](https://www.anchorterminal.com/compare/boxlang-ai-vs-strands-agents.md)\n- [BoxLang AI vs TradingAgents](https://www.anchorterminal.com/compare/boxlang-ai-vs-tradingagents.md)\n- [BoxLang AI vs AI SDK](https://www.anchorterminal.com/compare/boxlang-ai-vs-vercel-ai-sdk.md)\n- [Claude Agent SDK vs LlamaIndex Framework](https://www.anchorterminal.com/compare/claude-agent-sdk-vs-llamaindex.md)\n- [CrewAI vs LlamaIndex Framework](https://www.anchorterminal.com/compare/crewai-vs-llamaindex.md)\n- [Cursor Agent SDK vs LlamaIndex Framework](https://www.anchorterminal.com/compare/cursor-agent-sdk-vs-llamaindex.md)\n- [Docker Agent vs LlamaIndex Framework](https://www.anchorterminal.com/compare/docker-agent-vs-llamaindex.md)\n- [Agent Development Kit (ADK) vs LlamaIndex Framework](https://www.anchorterminal.com/compare/google-adk-vs-llamaindex.md)\n- [guilds.run vs LlamaIndex Framework](https://www.anchorterminal.com/compare/guilds-run-vs-llamaindex.md)\n- [LangGraph vs LlamaIndex Framework](https://www.anchorterminal.com/compare/langgraph-vs-llamaindex.md)\n- [LlamaIndex Framework vs Mastra](https://www.anchorterminal.com/compare/llamaindex-vs-mastra.md)\n- [LlamaIndex Framework vs Microsoft Agent Framework](https://www.anchorterminal.com/compare/llamaindex-vs-microsoft-agent-framework.md)\n- [LlamaIndex Framework vs OpenAI Agents SDK](https://www.anchorterminal.com/compare/llamaindex-vs-openai-agents-sdk.md)\n- [LlamaIndex Framework vs Pydantic AI](https://www.anchorterminal.com/compare/llamaindex-vs-pydantic-ai.md)\n- [LlamaIndex Framework vs smolagents](https://www.anchorterminal.com/compare/llamaindex-vs-smolagents.md)\n- [LlamaIndex Framework vs Strands Agents](https://www.anchorterminal.com/compare/llamaindex-vs-strands-agents.md)\n- [LlamaIndex Framework vs TradingAgents](https://www.anchorterminal.com/compare/llamaindex-vs-tradingagents.md)\n- [LlamaIndex Framework vs AI SDK](https://www.anchorterminal.com/compare/llamaindex-vs-vercel-ai-sdk.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": "2026-11-07", "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 LlamaIndex Framework", "url": "" } ], "description": "LlamaIndex Framework scores 70 (BB) 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", "LlamaIndex Framework BB 70", "scores" ], "h1": "BoxLang AI vs LlamaIndex Framework", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/boxlang-ai-vs-llamaindex", "published": "2026-10-01", "section": "tools", "title": "BoxLang AI vs LlamaIndex Framework for AI agents (2026)", "toc": null, "updated": "2026-11-07", "url": "https://www.anchorterminal.com/compare/boxlang-ai-vs-llamaindex" }, "tokens": { "markdown": 3550, "slim": 1530 }, "version": 1 }