{ "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": "BoxLang AI scores 65.8 (B) on agent readiness against TradingAgents's 64.7 (B), and leads in 5 of 7 scored categories. TradingAgents leads on payments \u0026 pricing.", "b": { "slug": "tradingagents", "name": "TradingAgents", "vendor": "Tauric Research", "vendorUrl": "https://tauric.ai", "kind": "framework", "category": "frameworks", "summary": "TradingAgents, from Tauric Research, is an open-source Python framework on LangGraph in which LLM agents for analysis, research debate, trading and risk review produce a five-tier rating and a report for one ticker and date.", "url": "https://www.anchorterminal.com/tools/tradingagents", "markdownUrl": "https://www.anchorterminal.com/tools/tradingagents.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/tradingagents.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/tradingagents.json", "dns": "tradingagents.grade.anchorterminal.com", "repo": "https://github.com/TauricResearch/TradingAgents", "license": "Apache-2.0", "transports": [], "packages": [], "auth": "api-key", "authNotes": "The framework has no account of its own. Each model provider's key is read from the environment or a .env file, which the package loads on import by walking up from the working directory. A ChatGPT Plus or Pro plan can be used instead through OpenAI's sign-in for open-source apps (PKCE, dynamic client registration, loopback redirect), with tokens kept in ~/.tradingagents/chatgpt-auth.json readable only by its owner and revoked by `tradingagents logout chatgpt`. Bedrock uses AWS credentials. Alpha Vantage, FRED and TypeSafe's Jev take optional keys; Yahoo Finance, SEC EDGAR, Reddit, StockTwits and Polymarket need none.", "pricing": "free", "pricingNotes": "Free under Apache 2.0, with nothing to buy from Tauric Research to run it. Each run calls the chosen model provider many times (four analysts, a debate, a trader, three risk debaters and two managers by default), billed by that provider, or counted against a ChatGPT plan's usage limits. Alpha Vantage and Jev bill on their own terms when their keys are set. Tauric Research's hosted services at tauric.ai are invitation or enterprise access with no public price, and are not this listing (checked 2026-10-25).", "priceSummary": "Free · OSS", "where": "library", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the source, README or changelog of v0.7.0 (checked 2026-10-25).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 114000, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-25" }, "docsUrl": "https://github.com/TauricResearch/TradingAgents#readme", "capabilities": [ "agent.framework", "agent.multi-agent", "agent.durable" ], "tags": [ "framework", "python", "langgraph", "open-source", "apache-2.0", "self-hosted", "local", "cli", "docker", "free", "pre-1.0" ], "lastRelease": "2026-10-16", "graded": true, "anchor": { "graded": true, "score": 64.7, "grade": "B", "agentReady": false, "rank": 381, "ranked": true, "rankOf": 1260, "categoryRank": 11, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 61, "maintenance": 82, "payments": 60, "reliability": 67, "schema": 61, "security": 62, "transparency": 68 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-25" }, "negative": 0, "verdict": "An Apache 2.0 LangGraph framework at 0.7.0 with six releases in 90 days, a dated changelog with upgrade notes, a public test matrix and point-in-time rules for historical runs. It has no MCP client or server, no PyPI package and no documentation beyond the README, and its output is a model-written rating that places no orders.", "bestFor": "Researchers who want a fixed multi-agent analysis of one listed instrument or crypto pair on a date, with point-in-time data for backtests, and who will run Python.", "strengths": [ "Apache 2.0, with six releases between 30 August and 16 October 2026 and \"Upgrading from\" notes in a dated changelog", "CI runs 982 test functions on Python 3.11 to 3.14, a clean-install import check and Ruff, passing on main on 25 October 2026", "Past-dated runs read SEC EDGAR statements as filed on that date and withhold Yahoo statements and insider trades that can't be dated", "Runs headless from flags and TRADINGAGENTS_* variables, and checkpoint resume and backtest run IDs skip work already done", "Places no orders and holds no broker credentials; tools only read market, filing, news and social data" ], "weaknesses": [ "No MCP client or MCP server, so an agent drives it only through Python or the CLI", "Not on PyPI; installs from a clone, Docker or the wheel attached to each GitHub release since 0.7.0", "Documentation is the README and changelog only, with no API reference or llms.txt", "0.5.1, a patch release, moved import paths and removed classes without a deprecation period", "News, Reddit and StockTwits text goes into prompts with no documented guidance on prompt injection" ], "agentNotes": [ "Run headless with `tradingagents --ticker \u003cT\u003e --date \u003cYYYY-MM-DD\u003e --analysts market,news,fundamentals --save --no-show`; a missing answer stops the run and names the flag", "Guard on the REVIEW signal before mapping `propagate()`'s decision to a rating; it means no rating could be parsed", "Set SEC_EDGAR_USER_AGENT to the operator's own name and address before fetching US fundamentals", "Keep provider keys out of the working directory tree unless intended, since the package loads the nearest .env on import", "Treat the rating as model output for research; the framework places no orders and its results vary between runs" ], "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": 64.7 } ], "editorialScores": { "ergonomics": 61, "maintenance": 82, "payments": 60, "reliability": 67, "schema": 61, "security": 62, "transparency": 73 }, "provenanceScore": 62, "checked": { "categories": { "ergonomics": "2026-10-25", "maintenance": "2026-10-25", "payments": "2026-10-25", "reliability": "2026-10-25", "schema": "2026-10-25", "security": "2026-10-25", "transparency": "2026-10-25" }, "last": "2026-10-25", "lastMoved": "2026-10-30", "oldest": "2026-10-25", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "git clone https://github.com/TauricResearch/TradingAgents.git \u0026\u0026 cd TradingAgents \u0026\u0026 pip install ." }, "letme": { "capability": "https://letme.dev/agent.framework", "tool": "https://letme.dev/tradingagents" }, "area": "frameworks", "provenance": { "legalEntity": "Tauric Research", "domain": "tauric.ai", "domainRegistered": "2025-03-26", "endpointOnVendorDomain": null, "terms": "https://tauric.ai/terms", "privacy": "https://tauric.ai/privacy", "statusPage": "", "changelog": "https://github.com/TauricResearch/TradingAgents/blob/main/CHANGELOG.md", "securityTxt": "none", "checked": "2026-10-25", "notes": [ "The terms and privacy policy, both effective 23 October 2026, name Tauric Research and California law and cover tauric.ai's hosted services. No legal form or address was found. The framework itself is under Apache 2.0, whose LICENSE file carries no copyright line.", "tauric.ai/.well-known/security.txt returns the site's HTML page, not a security.txt. The repository's issue template sends security reports to GitHub private vulnerability reporting; there is no SECURITY.md.", "RDAP gives tauric.ai a registration date of 2025-03-26.", "No status page; the software runs on the user's machine." ], "score": 62 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/tradingagents.json", "live": { "slug": "tradingagents", "versions": [ { "registry": "github", "name": "TauricResearch/TradingAgents", "version": "v0.7.1", "released": "2026-10-27", "seenAt": "2026-11-01T17:39:45.606021114Z" } ], "githubStars": 119415, "securityTxt": { "url": "https://tauric.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-01T15:42:22.950596073Z" }, "domain": { "domain": "tauric.ai", "registered": "2025-03-26", "source": "https://rdap.identitydigital.services/rdap/domain/tauric.ai", "checkedAt": "2026-11-01T14:17:50.711505753Z" }, "pages": [ { "url": "https://raw.githubusercontent.com/TauricResearch/TradingAgents/main/CHANGELOG.md", "kind": "deprecations", "status": 304, "checkedAt": "2026-11-01T06:52:05.064001432Z", "changedAt": "2026-10-28T04:42:43.2803853Z", "fingerprint": "17477e48440b" }, { "url": "https://tauric.ai/privacy", "kind": "privacy", "status": 200, "checkedAt": "2026-11-01T06:54:15.350697086Z", "changedAt": "2026-11-01T06:54:15.350697086Z", "fingerprint": "6385c4901736" }, { "url": "https://tauric.ai/terms", "kind": "terms", "status": 200, "checkedAt": "2026-11-01T06:54:17.903530576Z", "changedAt": "2026-11-01T06:54:17.903530576Z", "fingerprint": "d221cc2aef3f" } ], "github": { "repo": "tauricresearch/tradingagents", "checkedAt": "2026-10-26T07:06:21.979903862Z", "stars": 114957, "archived": false, "issuesEnabled": true, "pushedAt": "2026-10-16T21:38:46Z", "openIssues": 44, "openPRs": 109, "issuesOpened90d": 103, "issuesClosed90d": 216, "prsMerged90d": 14, "ci": { "branch": "main", "runs": 42, "success": 42, "failure": 0, "other": 0, "latest": "success", "latestAt": "2026-10-16T21:40:10Z" }, "replies": { "sampled": 25, "unanswered": 7, "medianDays": 3.2 } }, "updatedAt": "2026-11-01T17:39:45.606021114Z" } }, "edges": [ { "by": 13, "category": "ergonomics", "leads": "boxlang-ai", "name": "Agent ergonomics", "reasons": { "a": "Framework reading, scored on what a tool-calling agent with MCP takes. An agent with an MCP server is one `aiAgent()` call with `mcpServers`, and `toolFilter` and `prefix` limit what each server adds. Skills can load lazily, but `autoLoadSkills` is on by default and injects every SKILL.md under /.agents/skills into every agent (20 of 25). MaxToolCallsMiddleware caps tool calls, window and summary memory bound history by messages or tokens, `withMaxResponseBytes` caps MCP answers and `listTools( cursor )` pages tools (17 of 20). Named exceptions (ProviderError, UnsupportedCapability, InvalidArgument, MCPCommandRefused, BXAI.SecurityViolation) but no reference page, and the changelog says a timed-out call still surfaces as a JSON parse error (12 of 20). RetryMiddleware with exponential backoff, approval resumes that don't replay the model call or rerun executed tools, and a stdio client that never repeats an in-flight call. MCP tool annotations such as readOnlyHint aren't read (15 of 20). An agent needs a name and works with defaults, and a mock provider runs with no key, but it is one language (10 of 15). 74 in all.", "b": "Framework reading, scored on what an outside agent needs to call it. No MCP client or server, so it can't be attached as tools; a run is four lines of Python (`TradingAgentsGraph(config=...).propagate(ticker, date)`) or one headless CLI command with flags (10 of 25). Analyst selection, debate and risk rounds (default 1), `max_tool_rounds` (20), `max_recur_limit` (100), article limits and `--no-html` size a run (14 of 20). A typed vendor error hierarchy separates unavailable from absent data, the headless CLI names the missing flag before a run starts, and an unparseable decision returns REVIEW rather than Hold (15 of 20). Checkpoint resume is opt-in, a backtest rerun with the same `run_id` skips finished cells, and settlement writes each decision once; nothing writes to an outside system (15 of 20). Sensible defaults, but the default provider is OpenAI's GPT-6 models with a key, and Python only (7 of 15)." }, "scores": { "a": 74, "b": 61 } }, { "by": 10, "category": "schema", "leads": "boxlang-ai", "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. No API reference or docs site. Typed interfaces exist in the source, Pydantic models for the research manager's, trader's and portfolio manager's outputs and Annotated signatures on the twelve data tools, with no py.typed marker (10 of 25). The README and changelog are Markdown in the repository; no llms.txt (4 of 10). The README states limits plainly, that runs vary, which statements past-dated runs withhold and why, and that it is a research tool, not advice (15 of 20). Configuration is a plain dict of string keys, though environment overrides are coerced to the default's type and fail loudly on a bad value (8 of 15). Runnable Python and CLI examples throughout the README; the vendor error hierarchy is documented only in source docstrings (9 of 15). Dated changelog for every release from 0.1.0 with upgrade notes (15)." }, "scores": { "a": 71, "b": 61 } }, { "by": 10, "category": "payments", "leads": "tradingagents", "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 $4,999 a server or node a year, plan pricing rather than per unit (10). The Apache-2.0 module installs with no card (20) and no account or sign-up (20). 50 in all.", "b": "No payment protocol (0). Self-hosted rule. Free under Apache 2.0 with nothing to buy from Tauric Research to run it (20), no card (20) and no Tauric account (20). Tauric Research's hosted services at tauric.ai are invitation or enterprise access with no public price and aren't the graded surface. Model provider costs are the user's." }, "scores": { "a": 50, "b": 60 } }, { "by": 9, "category": "security", "leads": "boxlang-ai", "name": "Security \u0026 auth", "reasons": { "a": "Framework reading. 30 for what leaves the machine and credentials, 20 for approvals and sandboxing, 15 for prompt injection, 15 for audit and 20 for the security programme. No telemetry in the module's source, requests go only to configured providers, keys come from settings or environment variables, and request logging is off by default. 3.4.0 fixed a Gemini key leaking into logs through the request URL (27 of 30). Approval is enforced in code by HumanInTheLoopMiddleware with five policies, GuardrailMiddleware blocks tools by name and argument pattern, and stdio commands never use a shell. All of it is opt-in. `allowedCommands` allows any executable by default, FileSystemTools allows any path without `allowedPaths`, and the MCP server has no authentication unless configured (12 of 20). Unicode hygiene and fencing of `${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": "Framework reading. 30 for what leaves the machine and how credentials are held, 20 for least privilege and approvals, 15 for prompt injection, 15 for audit and 20 for the security programme. Keys are read from the environment, and the package loads the nearest .env on import by walking up from the working directory. The ChatGPT sign-in uses PKCE and dynamic client registration, keeps tokens in a 0600 file and revokes them on logout. The only calls of its own are the interactive CLI's daily release and notice check, with no run data, off without a terminal or with TRADINGAGENTS_NO_UPDATE_CHECK=1. SEC EDGAR gets a placeholder contact address unless one is set (24 of 30). It places no orders and holds no broker credentials, the data tools only read, and every ticker is validated before it is used in a file path. No approval hooks, which nothing in it needs (14 of 20). News, Reddit and StockTwits text goes into prompts. The source names prompt injection as the reason for path validation, but no guidance on injection was found in the README (5 of 15). Saved reports record the run's settings and each agent's report, the memory log keeps every decision, and `debug=True` streams the graph (11 of 15). Security reports go to GitHub private vulnerability reporting per the issue template, and the changelog has Security sections for a langchain-core patch and a dependency removed over CVE-2026-22218. No SECURITY.md, no security.txt on tauric.ai, no bounty, and the repository's advisories page wasn't read (8 of 20)." }, "scores": { "a": 71, "b": 62 } } ], "facts": [ { "a": "Agent framework", "b": "Agent framework", "name": "Kind" }, { "a": "Ortus Solutions", "b": "Tauric Research", "name": "Vendor" }, { "a": "no (local only)", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "", "b": "", "name": "Transports" }, { "a": "None", "b": "API key", "name": "Auth" }, { "a": "Free", "b": "Free", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Apache-2.0", "b": "Apache-2.0", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "no", "name": "llms.txt" }, { "a": "2026-10-20", "b": "2026-10-16", "name": "Last release" }, { "a": "no date given", "b": "2026-10-23", "name": "Terms last updated" }, { "a": "no date given", "b": "2026-10-23", "name": "Privacy policy last updated" }, { "a": "not found in the text", "b": "not found in the text", "name": "Customer content may train models" }, { "a": "not found in the text", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "not found in the text", "b": "not found in the text", "name": "Terms restrict benchmarking" }, { "a": "not found in the text", "b": "not found in the text", "name": "Terms or service can change without notice" }, { "a": "not found in the text", "b": "not found in the text", "name": "Arbitration or class-action waiver" }, { "a": "none", "b": "114k stars", "name": "Popularity" } ], "faq": [ { "answer": "BoxLang AI scores 65.8 (B) on agent readiness against TradingAgents's 64.7 (B), and leads in 5 of 7 scored categories. TradingAgents leads on payments \u0026 pricing.", "question": "Which is better for AI agents, BoxLang AI or TradingAgents?" }, { "answer": "Yes. BoxLang AI is open source (Apache-2.0). TradingAgents is open source (Apache-2.0).", "question": "Are BoxLang AI and TradingAgents open source?" } ], "goodFor": [ { "aheadOn": [ "Schema \u0026 documentation, 71 against 61", "Agent ergonomics, 74 against 61", "Security \u0026 auth, 71 against 62" ], "also": [ "No key needed to call it" ], "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": [ "Payments \u0026 pricing, 60 against 50" ], "also": [ "No incidents deducted, where BoxLang AI loses 3 points for them" ], "goodFor": "Researchers who want a fixed multi-agent analysis of one listed instrument or crypto pair on a date, with point-in-time data for backtests, and who will run Python.", "slug": "tradingagents", "watchFor": "No MCP client or MCP server, so an agent drives it only through Python or the CLI" } ], "history": { "boxlang-ai": null, "tradingagents": [ { "causes": [ "method" ], "date": "2026-10-30", "delta": -0.1, "from": 64.8, "fromGrade": "B", "to": 64.7, "toGrade": "B" }, { "causes": [ "method" ], "date": "2026-10-27", "delta": 0.1, "from": 64.7, "fromGrade": "B", "to": 64.8, "toGrade": "B" } ] }, "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-tradingagents.json", "title": "AgentOS vs TradingAgents", "url": "https://www.anchorterminal.com/compare/agentos-vs-tradingagents" }, { "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-tradingagents.json", "title": "Agno vs TradingAgents", "url": "https://www.anchorterminal.com/compare/agno-vs-tradingagents" }, { "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-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/claude-agent-sdk-vs-tradingagents.json", "title": "Claude Agent SDK vs TradingAgents", "url": "https://www.anchorterminal.com/compare/claude-agent-sdk-vs-tradingagents" }, { "json": "https://www.anchorterminal.com/compare/crewai-vs-tradingagents.json", "title": "CrewAI vs TradingAgents", "url": "https://www.anchorterminal.com/compare/crewai-vs-tradingagents" }, { "json": "https://www.anchorterminal.com/compare/cursor-agent-sdk-vs-tradingagents.json", "title": "Cursor Agent SDK vs TradingAgents", "url": "https://www.anchorterminal.com/compare/cursor-agent-sdk-vs-tradingagents" }, { "json": "https://www.anchorterminal.com/compare/docker-agent-vs-tradingagents.json", "title": "Docker Agent vs TradingAgents", "url": "https://www.anchorterminal.com/compare/docker-agent-vs-tradingagents" }, { "json": "https://www.anchorterminal.com/compare/google-adk-vs-tradingagents.json", "title": "Agent Development Kit (ADK) vs TradingAgents", "url": "https://www.anchorterminal.com/compare/google-adk-vs-tradingagents" }, { "json": "https://www.anchorterminal.com/compare/guilds-run-vs-tradingagents.json", "title": "guilds.run vs TradingAgents", "url": "https://www.anchorterminal.com/compare/guilds-run-vs-tradingagents" }, { "json": "https://www.anchorterminal.com/compare/langgraph-vs-tradingagents.json", "title": "LangGraph vs TradingAgents", "url": "https://www.anchorterminal.com/compare/langgraph-vs-tradingagents" }, { "json": "https://www.anchorterminal.com/compare/microsoft-agent-framework-vs-tradingagents.json", "title": "Microsoft Agent Framework vs TradingAgents", "url": "https://www.anchorterminal.com/compare/microsoft-agent-framework-vs-tradingagents" }, { "json": "https://www.anchorterminal.com/compare/openai-agents-sdk-vs-tradingagents.json", "title": "OpenAI Agents SDK vs TradingAgents", "url": "https://www.anchorterminal.com/compare/openai-agents-sdk-vs-tradingagents" }, { "json": "https://www.anchorterminal.com/compare/pydantic-ai-vs-tradingagents.json", "title": "Pydantic AI vs TradingAgents", "url": "https://www.anchorterminal.com/compare/pydantic-ai-vs-tradingagents" } ], "panel": null, "scores": [ { "boxlang-ai": 66, "by": 1, "edge": "tradingagents", "key": "reliability", "name": "Reliability", "tradingagents": 67, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "boxlang-ai": 71, "by": 10, "edge": "boxlang-ai", "key": "schema", "name": "Schema \u0026 documentation", "tradingagents": 61, "weight": 13 }, { "boxlang-ai": 74, "by": 13, "edge": "boxlang-ai", "key": "ergonomics", "name": "Agent ergonomics", "tradingagents": 61, "weight": 13 }, { "boxlang-ai": 71, "by": 9, "edge": "boxlang-ai", "key": "security", "name": "Security \u0026 auth", "tradingagents": 62, "weight": 14 }, { "boxlang-ai": 50, "by": 10, "edge": "tradingagents", "key": "payments", "name": "Payments \u0026 pricing", "tradingagents": 60, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "boxlang-ai": 83, "by": 1, "edge": "boxlang-ai", "key": "maintenance", "name": "Maintenance \u0026 community", "tradingagents": 82, "weight": 7 }, { "boxlang-ai": 70, "by": 2, "edge": "boxlang-ai", "key": "transparency", "name": "Transparency \u0026 trust", "tradingagents": 68, "weight": 7 } ], "summary": "BoxLang AI scores 65.8 (B) on agent readiness against TradingAgents's 64.7 (B), and leads in 5 of 7 scored categories. TradingAgents leads on payments \u0026 pricing. 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.", "tradingagents": "An Apache 2.0 LangGraph framework at 0.7.0 with six releases in 90 days, a dated changelog with upgrade notes, a public test matrix and point-in-time rules for historical runs. It has no MCP client or server, no PyPI package and no documentation beyond the README, and its output is a model-written rating that places no orders." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/boxlang-ai-vs-tradingagents", "json": "https://www.anchorterminal.com/compare/boxlang-ai-vs-tradingagents.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/boxlang-ai-vs-tradingagents.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/boxlang-ai-vs-tradingagents.min.md" }, "markdown": "BoxLang AI scores 65.8 (B) on agent readiness against TradingAgents's 64.7 (B), and leads in 5 of 7 scored categories. TradingAgents leads on payments \u0026 pricing. 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- TradingAgents: grade B, 64.7/100, rank #381 of 1260. Markdown https://www.anchorterminal.com/tools/tradingagents.md · JSON https://www.anchorterminal.com/api/v1/tools/tradingagents.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- Schema \u0026 documentation, 71 against 61\n- Agent ergonomics, 74 against 61\n- Security \u0026 auth, 71 against 62\n\nAlso in its favour:\n- No key needed to call it\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### TradingAgents (B)\n\nGood for: Researchers who want a fixed multi-agent analysis of one listed instrument or crypto pair on a date, with point-in-time data for backtests, and who will run Python.\n\nAhead on:\n- Payments \u0026 pricing, 60 against 50\n\nAlso in its favour:\n- No incidents deducted, where BoxLang AI loses 3 points for them\n\nWatch for: No MCP client or MCP server, so an agent drives it only through Python or the CLI\n\n\n## Why the edge\n\n### Agent ergonomics: BoxLang AI +13\n\n- BoxLang AI (74): Framework reading, scored on what a tool-calling agent with MCP takes. An agent with an MCP server is one `aiAgent()` call with `mcpServers`, and `toolFilter` and `prefix` limit what each server adds. Skills can load lazily, but `autoLoadSkills` is on by default and injects every SKILL.md under /.agents/skills into every agent (20 of 25). MaxToolCallsMiddleware caps tool calls, window and summary memory bound history by messages or tokens, `withMaxResponseBytes` caps MCP answers and `listTools( cursor )` pages tools (17 of 20). Named exceptions (ProviderError, UnsupportedCapability, InvalidArgument, MCPCommandRefused, BXAI.SecurityViolation) but no reference page, and the changelog says a timed-out call still surfaces as a JSON parse error (12 of 20). RetryMiddleware with exponential backoff, approval resumes that don't replay the model call or rerun executed tools, and a stdio client that never repeats an in-flight call. MCP tool annotations such as readOnlyHint aren't read (15 of 20). An agent needs a name and works with defaults, and a mock provider runs with no key, but it is one language (10 of 15). 74 in all.\n- TradingAgents (61): Framework reading, scored on what an outside agent needs to call it. No MCP client or server, so it can't be attached as tools; a run is four lines of Python (`TradingAgentsGraph(config=...).propagate(ticker, date)`) or one headless CLI command with flags (10 of 25). Analyst selection, debate and risk rounds (default 1), `max_tool_rounds` (20), `max_recur_limit` (100), article limits and `--no-html` size a run (14 of 20). A typed vendor error hierarchy separates unavailable from absent data, the headless CLI names the missing flag before a run starts, and an unparseable decision returns REVIEW rather than Hold (15 of 20). Checkpoint resume is opt-in, a backtest rerun with the same `run_id` skips finished cells, and settlement writes each decision once; nothing writes to an outside system (15 of 20). Sensible defaults, but the default provider is OpenAI's GPT-6 models with a key, and Python only (7 of 15).\n\n### Schema \u0026 documentation: BoxLang AI +10\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- TradingAgents (61): Framework reading. No API reference or docs site. Typed interfaces exist in the source, Pydantic models for the research manager's, trader's and portfolio manager's outputs and Annotated signatures on the twelve data tools, with no py.typed marker (10 of 25). The README and changelog are Markdown in the repository; no llms.txt (4 of 10). The README states limits plainly, that runs vary, which statements past-dated runs withhold and why, and that it is a research tool, not advice (15 of 20). Configuration is a plain dict of string keys, though environment overrides are coerced to the default's type and fail loudly on a bad value (8 of 15). Runnable Python and CLI examples throughout the README; the vendor error hierarchy is documented only in source docstrings (9 of 15). Dated changelog for every release from 0.1.0 with upgrade notes (15).\n\n### Payments \u0026 pricing: TradingAgents +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 $4,999 a server or node a year, plan pricing rather than per unit (10). The Apache-2.0 module installs with no card (20) and no account or sign-up (20). 50 in all.\n- TradingAgents (60): No payment protocol (0). Self-hosted rule. Free under Apache 2.0 with nothing to buy from Tauric Research to run it (20), no card (20) and no Tauric account (20). Tauric Research's hosted services at tauric.ai are invitation or enterprise access with no public price and aren't the graded surface. Model provider costs are the user's.\n\n### Security \u0026 auth: BoxLang AI +9\n\n- BoxLang AI (71): Framework reading. 30 for what leaves the machine and credentials, 20 for approvals and sandboxing, 15 for prompt injection, 15 for audit and 20 for the security programme. No telemetry in the module's source, requests go only to configured providers, keys come from settings or environment variables, and request logging is off by default. 3.4.0 fixed a Gemini key leaking into logs through the request URL (27 of 30). Approval is enforced in code by HumanInTheLoopMiddleware with five policies, GuardrailMiddleware blocks tools by name and argument pattern, and stdio commands never use a shell. All of it is opt-in. `allowedCommands` allows any executable by default, FileSystemTools allows any path without `allowedPaths`, and the MCP server has no authentication unless configured (12 of 20). Unicode hygiene and fencing of `${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- TradingAgents (62): Framework reading. 30 for what leaves the machine and how credentials are held, 20 for least privilege and approvals, 15 for prompt injection, 15 for audit and 20 for the security programme. Keys are read from the environment, and the package loads the nearest .env on import by walking up from the working directory. The ChatGPT sign-in uses PKCE and dynamic client registration, keeps tokens in a 0600 file and revokes them on logout. The only calls of its own are the interactive CLI's daily release and notice check, with no run data, off without a terminal or with TRADINGAGENTS_NO_UPDATE_CHECK=1. SEC EDGAR gets a placeholder contact address unless one is set (24 of 30). It places no orders and holds no broker credentials, the data tools only read, and every ticker is validated before it is used in a file path. No approval hooks, which nothing in it needs (14 of 20). News, Reddit and StockTwits text goes into prompts. The source names prompt injection as the reason for path validation, but no guidance on injection was found in the README (5 of 15). Saved reports record the run's settings and each agent's report, the memory log keeps every decision, and `debug=True` streams the graph (11 of 15). Security reports go to GitHub private vulnerability reporting per the issue template, and the changelog has Security sections for a langchain-core patch and a dependency removed over CVE-2026-22218. No SECURITY.md, no security.txt on tauric.ai, no bounty, and the repository's advisories page wasn't read (8 of 20).\n\n## Score by category\n\n| Category | Weight | BoxLang AI | TradingAgents | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 66 | 67 | TradingAgents +1 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 71 | 61 | BoxLang AI +10 |\n| Agent ergonomics | 13% (16.2 this run) | 74 | 61 | BoxLang AI +13 |\n| Security \u0026 auth | 14% (17.5 this run) | 71 | 62 | BoxLang AI +9 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 50 | 60 | TradingAgents +10 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 83 | 82 | BoxLang AI +1 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 70 | 68 | BoxLang AI +2 |\n| Negative events | ≤15 | -3 | 0 | |\n| **Total** | | **65.8 · B** | **64.7 · B** | |\n\n## Facts side by side\n\n| Fact | BoxLang AI | TradingAgents |\n| --- | --- | --- |\n| Kind | Agent framework | Agent framework |\n| Vendor | Ortus Solutions | Tauric Research |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | | |\n| Auth | None | API key |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | Apache-2.0 | Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | yes | no |\n| Last release | 2026-10-20 | 2026-10-16 |\n| Terms last updated | no date given | 2026-10-23 |\n| Privacy policy last updated | no date given | 2026-10-23 |\n| Customer content may train models | not found in the text | not found in the text |\n| Terms restrict automated access | not found in the text | not found in the text |\n| Terms restrict benchmarking | not found in the text | not found in the text |\n| Terms or service can change without notice | not found in the text | not found in the text |\n| Arbitration or class-action waiver | not found in the text | not found in the text |\n| Popularity | none | 114k stars |\n\n## How the scores have moved\n\n### BoxLang AI\n\nNo score change since it was listed.\n\n### TradingAgents\n\n- -0.1 on 30 October 2026: checklist\n- +0.1 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**TradingAgents.** An Apache 2.0 LangGraph framework at 0.7.0 with six releases in 90 days, a dated changelog with upgrade notes, a public test matrix and point-in-time rules for historical runs. It has no MCP client or server, no PyPI package and no documentation beyond the README, and its output is a model-written rating that places no orders.\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### TradingAgents\n\n1. Run headless with `tradingagents --ticker \u003cT\u003e --date \u003cYYYY-MM-DD\u003e --analysts market,news,fundamentals --save --no-show`; a missing answer stops the run and names the flag\n2. Guard on the REVIEW signal before mapping `propagate()`'s decision to a rating; it means no rating could be parsed\n3. Set SEC_EDGAR_USER_AGENT to the operator's own name and address before fetching US fundamentals\n4. Keep provider keys out of the working directory tree unless intended, since the package loads the nearest .env on import\n5. Treat the rating as model output for research; the framework places no orders and its results vary between runs\n\n## Questions\n\n### Which is better for AI agents, BoxLang AI or TradingAgents?\n\nBoxLang AI scores 65.8 (B) on agent readiness against TradingAgents's 64.7 (B), and leads in 5 of 7 scored categories. TradingAgents leads on payments \u0026 pricing.\n\n### Are BoxLang AI and TradingAgents open source?\n\nYes. BoxLang AI is open source (Apache-2.0). TradingAgents is open source (Apache-2.0).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/boxlang-ai-vs-tradingagents.json, and with the fewest tokens: https://www.anchorterminal.com/compare/boxlang-ai-vs-tradingagents.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"boxlang-ai\", \"b\": \"tradingagents\"}`. From a terminal: `anchor compare boxlang-ai tradingagents`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/boxlang-ai.json and https://www.anchorterminal.com/api/v1/tools/tradingagents.json\n\n## Other comparisons with BoxLang AI or TradingAgents\n\n- [AgentOS vs BoxLang AI](https://www.anchorterminal.com/compare/agentos-vs-boxlang-ai.md)\n- [AgentOS vs TradingAgents](https://www.anchorterminal.com/compare/agentos-vs-tradingagents.md)\n- [Agno vs BoxLang AI](https://www.anchorterminal.com/compare/agno-vs-boxlang-ai.md)\n- [Agno vs TradingAgents](https://www.anchorterminal.com/compare/agno-vs-tradingagents.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 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- [Claude Agent SDK vs TradingAgents](https://www.anchorterminal.com/compare/claude-agent-sdk-vs-tradingagents.md)\n- [CrewAI vs TradingAgents](https://www.anchorterminal.com/compare/crewai-vs-tradingagents.md)\n- [Cursor Agent SDK vs TradingAgents](https://www.anchorterminal.com/compare/cursor-agent-sdk-vs-tradingagents.md)\n- [Docker Agent vs TradingAgents](https://www.anchorterminal.com/compare/docker-agent-vs-tradingagents.md)\n- [Agent Development Kit (ADK) vs TradingAgents](https://www.anchorterminal.com/compare/google-adk-vs-tradingagents.md)\n- [guilds.run vs TradingAgents](https://www.anchorterminal.com/compare/guilds-run-vs-tradingagents.md)\n- [LangGraph vs TradingAgents](https://www.anchorterminal.com/compare/langgraph-vs-tradingagents.md)\n- [Microsoft Agent Framework vs TradingAgents](https://www.anchorterminal.com/compare/microsoft-agent-framework-vs-tradingagents.md)\n- [OpenAI Agents SDK vs TradingAgents](https://www.anchorterminal.com/compare/openai-agents-sdk-vs-tradingagents.md)\n- [Pydantic AI vs TradingAgents](https://www.anchorterminal.com/compare/pydantic-ai-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 TradingAgents", "url": "" } ], "description": "BoxLang AI scores 65.8 (B) to TradingAgents's 64.7 (B) for agent frameworks. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "BoxLang AI B 65.8", "TradingAgents B 64.7", "scores" ], "h1": "BoxLang AI vs TradingAgents", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/boxlang-ai-vs-tradingagents", "published": "2026-10-01", "section": "tools", "title": "BoxLang AI vs TradingAgents for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-11-01", "url": "https://www.anchorterminal.com/compare/boxlang-ai-vs-tradingagents" }, "tokens": { "markdown": 4500, "slim": 2530 }, "version": 1 }