{ "data": { "a": { "slug": "langgraph", "name": "LangGraph", "vendor": "LangChain", "vendorUrl": "https://www.langchain.com", "kind": "framework", "category": "frameworks", "summary": "Low-level runtime for long-running, stateful agent graphs with checkpointed persistence, human-in-the-loop, memory and streaming.", "url": "https://www.anchorterminal.com/tools/langgraph", "markdownUrl": "https://www.anchorterminal.com/tools/langgraph.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/langgraph.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/langgraph.json", "repo": "https://github.com/langchain-ai/langgraph", "license": "MIT", "transports": [], "packages": [ { "registry": "pypi", "name": "langgraph" }, { "registry": "npm", "name": "@langchain/langgraph" } ], "auth": "none", "authNotes": "A library. Credentials are for whichever model and tools you wire in.", "pricing": "free", "pricingNotes": "Free and open source. You pay for the model calls it makes. LangSmith for tracing is free for one developer, then $39 a seat a month. Deployment is metered.", "priceSummary": "Free · OSS", "where": "library", "x402": { "level": "no", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 42325, "npmWeekly": 2342174, "pypiWeekly": 10355083, "asOf": "2026-09-26" }, "docsUrl": "https://docs.langchain.com/oss/python/langgraph/overview", "llmsTxt": "https://docs.langchain.com/llms.txt", "capabilities": [ "agent.framework", "agent.multi-agent", "agent.durable", "agent.mcp-client" ], "tags": [ "framework", "python", "typescript", "open-source", "durable" ], "lastRelease": "2026-09-21", "graded": true, "anchor": { "graded": true, "score": 70.6, "grade": "BB", "agentReady": true, "rank": 163, "ranked": true, "rankOf": 1210, "categoryRank": 8, "methodology": "0.6", "run": "2026-10-01", "scores": { "ergonomics": 70, "maintenance": 90, "payments": 60, "reliability": 75, "schema": 89, "security": 60, "transparency": 79 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-01" }, "negative": -3, "negativeNotes": [ "2025-10-29 to 2025-12-09. Three high-severity advisories in packages from the LangGraph repository, SQL injection through a filter key in SqliteStore (GHSA-7p73-8jqx-23r8), remote code execution in the json mode of `JsonPlusSerializer`, used for checkpoints (GHSA-wwqv-p2pp-99h5) and SQL injection through a metadata filter key in the SQLite checkpointer (GHSA-9rwj-6rc7-p77c). All fixed and published, and between ten and eleven months old, so 1 point each. Five moderate advisories in 2026 weren't deducted. https://github.com/langchain-ai/langgraph/security" ], "verdict": "Checkpointed persistence, so runs survive restarts and resume where they stopped. No MCP client of its own. LangChain's langchain.mcp is in beta.", "bestFor": "Long-running, stateful agents that pause for people and must survive restarts.", "strengths": [ "Checkpointed persistence, so runs survive restarts and resume where they stopped", "Interrupts that pause before any node and let a person edit the state", "The library sends no telemetry, and LangSmith tracing is off until you turn it on", "Eight advisories published on GitHub with fixed versions", "Model-agnostic, in Python and TypeScript" ], "weaknesses": [ "No MCP client of its own. LangChain's langchain.mcp is in beta", "More code than the others for a plain tool-calling agent", "No guardrail primitive or sandbox in LangGraph itself", "416 open issues and 230 open pull requests", "The CLI sends an analytics event per command by default" ], "agentNotes": [ "Use a persistent checkpointer in production, not the in-memory one", "Move from langchain-mcp-adapters to langchain.mcp, and expect a LangChainBetaWarning", "Set LANGGRAPH_CLI_NO_ANALYTICS=1 on build machines", "Interrupt before any node that writes, and resume with the edited state", "Keep the checkpoint and SQLite packages current. Each had a high-severity advisory in late 2025" ], "metrics": { "kind": "library", "measured": false }, "reviewCount": 2, "avgRating": 3.5, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "BB", "methodology": "0.6", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 70.6 } ], "editorialScores": { "ergonomics": 70, "maintenance": 90, "payments": 60, "reliability": 75, "schema": 89, "security": 60, "transparency": 89 }, "provenanceScore": 68, "checked": { "categories": { "ergonomics": "2026-10-01", "maintenance": "2026-10-01", "payments": "2026-10-01", "reliability": "2026-10-01", "schema": "2026-10-01", "security": "2026-10-01", "transparency": "2026-10-01" }, "last": "2026-10-01", "oldest": "2026-10-01", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install langgraph # or: npm i @langchain/langgraph" }, "letme": { "capability": "https://letme.dev/agent.framework", "tool": "https://letme.dev/langgraph" }, "sameCompany": [ "langmem", "langsmith" ], "area": "frameworks", "unitPrices": [ { "item": "LangSmith Plus", "unit": "seat-month", "usd": 39, "note": "tracing and evaluation, one developer free" } ], "provenance": { "legalEntity": "LangChain, Inc.", "domain": "langchain.com", "domainRegistered": "2019-12-03", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://docs.langchain.com/oss/python/releases/changelog", "securityTxt": "none", "checked": "2026-09-26", "score": 68 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/langgraph.json", "live": { "slug": "langgraph", "versions": [ { "registry": "github", "name": "langchain-ai/langgraph", "version": "1.2.17", "released": "2026-10-24", "seenAt": "2026-10-25T09:00:30.236520371Z" }, { "registry": "npm", "name": "@langchain/langgraph", "version": "1.5.2", "seenAt": "2026-10-25T09:00:29.452765338Z" }, { "registry": "pypi", "name": "langgraph", "version": "1.2.17", "released": "2026-10-24", "seenAt": "2026-10-25T09:00:29.335755656Z" } ], "githubStars": 43859, "npmWeekly": 2326897, "pypiWeekly": 13250778, "securityTxt": { "url": "https://langchain.com/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-25T15:28:31.115521449Z" }, "llmsTxt": { "url": "https://docs.langchain.com/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-10-25T14:52:23.655069815Z" }, "domain": { "domain": "langchain.com", "registered": "2019-12-03", "source": "https://rdap.verisign.com/com/v1/domain/langchain.com", "checkedAt": "2026-10-25T14:02:19.021606496Z" }, "pages": [ { "url": "https://docs.langchain.com/oss/python/releases/changelog", "kind": "deprecations", "status": 200, "checkedAt": "2026-10-25T02:45:25.256404517Z", "changedAt": "2026-10-24T02:15:43.301510995Z", "fingerprint": "6bd4cf95f097" } ], "github": { "repo": "langchain-ai/langgraph", "checkedAt": "2026-10-19T06:21:39.597619751Z", "stars": 43480, "archived": false, "issuesEnabled": true, "pushedAt": "2026-10-18T19:18:52Z", "openIssues": 418, "openPRs": 161, "issuesOpened90d": 262, "issuesClosed90d": 229, "prsMerged90d": 186, "ci": { "branch": "main", "runs": 50, "success": 40, "failure": 8, "other": 2, "latest": "success", "latestAt": "2026-10-18T19:26:18Z" }, "advisories": [ { "ghsa": "GHSA-3fx2-cqw9-xr3c", "severity": "medium", "published": "2026-10-07T17:31:37Z" }, { "ghsa": "GHSA-4hm6-w6qq-w73v", "severity": "high", "published": "2026-09-28T14:44:55Z" }, { "ghsa": "GHSA-fvww-7h3r-vfhp", "cve": "CVE-2026-104873", "severity": "high", "published": "2026-08-28T14:30:41Z" }, { "ghsa": "GHSA-47pj-3jcm-6whg", "cve": "CVE-2026-71433", "severity": "medium", "published": "2026-07-30T19:46:53Z" }, { "ghsa": "GHSA-fjqc-hq36-qh5p", "cve": "CVE-2026-48775", "severity": "medium", "published": "2026-05-22T17:18:27Z" }, { "ghsa": "GHSA-w39p-vh2g-g8g5", "cve": "CVE-2026-48776", "severity": "medium", "published": "2026-05-22T17:18:22Z" }, { "ghsa": "GHSA-g48c-2wqr-h844", "cve": "CVE-2026-28277", "severity": "medium", "published": "2026-03-05T16:52:38Z" }, { "ghsa": "GHSA-mhr3-j7m5-c7c9", "cve": "CVE-2026-27794", "severity": "medium", "published": "2026-02-23T19:15:53Z" }, { "ghsa": "GHSA-9rwj-6rc7-p77c", "cve": "CVE-2025-67644", "severity": "high", "published": "2025-12-09T22:07:45Z" }, { "ghsa": "GHSA-wwqv-p2pp-99h5", "cve": "CVE-2025-64439", "severity": "high", "published": "2025-11-05T15:13:54Z" }, { "ghsa": "GHSA-7p73-8jqx-23r8", "cve": "CVE-2025-64104", "severity": "high", "published": "2025-10-29T18:02:57Z" } ], "replies": { "sampled": 25, "unanswered": 22, "medianDays": 8.2 } }, "updatedAt": "2026-10-25T15:28:31.115521449Z" } }, "answer": "LangGraph scores 70.6 (BB) on agent readiness against TradingAgents's 64.7 (B), and leads in 5 of 7 scored categories.", "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", "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": 388, "ranked": true, "rankOf": 1210, "categoryRank": 11, "methodology": "0.6", "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": "0.6", "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", "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", "securityTxt": { "url": "https://tauric.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-25T15:28:01.187774257Z" }, "updatedAt": "2026-10-25T15:28:01.187774257Z" } }, "facts": [ { "a": "Agent framework", "b": "Agent framework", "name": "Kind" }, { "a": "LangChain", "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": "MIT", "b": "Apache-2.0", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "no", "name": "llms.txt" }, { "a": "2026-09-21", "b": "2026-10-16", "name": "Last release" }, { "a": "no document linked", "b": "", "name": "Terms last updated" }, { "a": "no document linked", "b": "", "name": "Privacy policy last updated" }, { "a": "", "b": "", "name": "Customer content may train models" }, { "a": "", "b": "", "name": "Terms restrict automated access" }, { "a": "", "b": "", "name": "Terms restrict benchmarking" }, { "a": "", "b": "", "name": "Terms or service can change without notice" }, { "a": "", "b": "", "name": "Arbitration or class-action waiver" }, { "a": "42k stars, 2.3M npm/wk, 10.4M PyPI/wk", "b": "114k stars", "name": "Popularity" }, { "a": "3.5/5 (2)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "LangGraph scores 70.6 (BB) on agent readiness against TradingAgents's 64.7 (B), and leads in 5 of 7 scored categories.", "question": "Which is better for AI agents, LangGraph or TradingAgents?" }, { "answer": "Yes. LangGraph is open source (MIT). TradingAgents is open source (Apache-2.0).", "question": "Are LangGraph and TradingAgents open source?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 75 against 67", "Schema \u0026 documentation, 89 against 61", "Agent ergonomics, 70 against 61", "Maintenance \u0026 community, 90 against 82", "Transparency \u0026 trust, 79 against 68" ], "also": [ "Agent-ready, a grade of BB or better", "No key needed to call it" ], "goodFor": "Long-running, stateful agents that pause for people and must survive restarts.", "slug": "langgraph", "watchFor": "No MCP client of its own. LangChain's langchain.mcp is in beta" }, { "aheadOn": null, "also": [ "No incidents deducted, where LangGraph 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" } ], "job": { "capability": "agent.framework", "name": "Agent frameworks" }, "others": [ { "json": "https://www.anchorterminal.com/compare/agentos-vs-langgraph.json", "title": "AgentOS vs LangGraph", "url": "https://www.anchorterminal.com/compare/agentos-vs-langgraph" }, { "json": "https://www.anchorterminal.com/compare/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-langgraph.json", "title": "Agno vs LangGraph", "url": "https://www.anchorterminal.com/compare/agno-vs-langgraph" }, { "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/claude-agent-sdk-vs-langgraph.json", "title": "Claude Agent SDK vs LangGraph", "url": "https://www.anchorterminal.com/compare/claude-agent-sdk-vs-langgraph" }, { "json": "https://www.anchorterminal.com/compare/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-langgraph.json", "title": "CrewAI vs LangGraph", "url": "https://www.anchorterminal.com/compare/crewai-vs-langgraph" }, { "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/docker-agent-vs-langgraph.json", "title": "Docker Agent vs LangGraph", "url": "https://www.anchorterminal.com/compare/docker-agent-vs-langgraph" }, { "json": "https://www.anchorterminal.com/compare/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-langgraph.json", "title": "Agent Development Kit (ADK) vs LangGraph", "url": "https://www.anchorterminal.com/compare/google-adk-vs-langgraph" }, { "json": "https://www.anchorterminal.com/compare/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-langgraph.json", "title": "guilds.run vs LangGraph", "url": "https://www.anchorterminal.com/compare/guilds-run-vs-langgraph" }, { "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-microsoft-agent-framework.json", "title": "LangGraph vs Microsoft Agent Framework", "url": "https://www.anchorterminal.com/compare/langgraph-vs-microsoft-agent-framework" }, { "json": "https://www.anchorterminal.com/compare/langgraph-vs-openai-agents-sdk.json", "title": "LangGraph vs OpenAI Agents SDK", "url": "https://www.anchorterminal.com/compare/langgraph-vs-openai-agents-sdk" }, { "json": "https://www.anchorterminal.com/compare/langgraph-vs-pydantic-ai.json", "title": "LangGraph vs Pydantic AI", "url": "https://www.anchorterminal.com/compare/langgraph-vs-pydantic-ai" }, { "json": "https://www.anchorterminal.com/compare/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" } ], "scores": [ { "by": 8, "edge": "langgraph", "key": "reliability", "langgraph": 75, "name": "Reliability", "tradingagents": 67, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 28, "edge": "langgraph", "key": "schema", "langgraph": 89, "name": "Schema \u0026 documentation", "tradingagents": 61, "weight": 13 }, { "by": 9, "edge": "langgraph", "key": "ergonomics", "langgraph": 70, "name": "Agent ergonomics", "tradingagents": 61, "weight": 13 }, { "by": 2, "edge": "tradingagents", "key": "security", "langgraph": 60, "name": "Security \u0026 auth", "tradingagents": 62, "weight": 14 }, { "by": 0, "edge": "", "key": "payments", "langgraph": 60, "name": "Payments \u0026 pricing", "tradingagents": 60, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 8, "edge": "langgraph", "key": "maintenance", "langgraph": 90, "name": "Maintenance \u0026 community", "tradingagents": 82, "weight": 7 }, { "by": 11, "edge": "langgraph", "key": "transparency", "langgraph": 79, "name": "Transparency \u0026 trust", "tradingagents": 68, "weight": 7 } ], "summary": "LangGraph scores 70.6 (BB) on agent readiness against TradingAgents's 64.7 (B), and leads in 5 of 7 scored categories. Both do agent frameworks.", "tutorials": [], "verdicts": { "langgraph": "Checkpointed persistence, so runs survive restarts and resume where they stopped. No MCP client of its own. LangChain's langchain.mcp is in beta.", "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/langgraph-vs-tradingagents", "json": "https://www.anchorterminal.com/compare/langgraph-vs-tradingagents.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/langgraph-vs-tradingagents.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/langgraph-vs-tradingagents.min.md" }, "markdown": "LangGraph scores 70.6 (BB) on agent readiness against TradingAgents's 64.7 (B), and leads in 5 of 7 scored categories. Both do agent frameworks.\n\n- LangGraph: grade BB, 70.6/100, rank #163 of 1210. Markdown https://www.anchorterminal.com/tools/langgraph.md · JSON https://www.anchorterminal.com/api/v1/tools/langgraph.json\n- TradingAgents: grade B, 64.7/100, rank #388 of 1210. 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 66 frameworks comparisons: https://www.anchorterminal.com/compare/frameworks/index.md\n\n## Which one, for what\n\n### LangGraph (BB)\n\nGood for: Long-running, stateful agents that pause for people and must survive restarts.\n\nAhead on:\n- Reliability, 75 against 67\n- Schema \u0026 documentation, 89 against 61\n- Agent ergonomics, 70 against 61\n- Maintenance \u0026 community, 90 against 82\n- Transparency \u0026 trust, 79 against 68\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n- No key needed to call it\n\nWatch for: No MCP client of its own. LangChain's langchain.mcp is in beta\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\nAlso in its favour:\n- No incidents deducted, where LangGraph 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## Score by category\n\n| Category | Weight | LangGraph | TradingAgents | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 75 | 67 | LangGraph +8 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 89 | 61 | LangGraph +28 |\n| Agent ergonomics | 13% (16.2 this run) | 70 | 61 | LangGraph +9 |\n| Security \u0026 auth | 14% (17.5 this run) | 60 | 62 | TradingAgents +2 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 60 | 60 | even |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 90 | 82 | LangGraph +8 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 79 | 68 | LangGraph +11 |\n| Negative events | ≤15 | -3 | 0 | |\n| **Total** | | **70.6 · BB** | **64.7 · B** | |\n\n## Facts side by side\n\n| Fact | LangGraph | TradingAgents |\n| --- | --- | --- |\n| Kind | Agent framework | Agent framework |\n| Vendor | LangChain | 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 | MIT | Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | yes | no |\n| Last release | 2026-09-21 | 2026-10-16 |\n| Terms last updated | no document linked | |\n| Privacy policy last updated | no document linked | |\n| Customer content may train models | | |\n| Terms restrict automated access | | |\n| Terms restrict benchmarking | | |\n| Terms or service can change without notice | | |\n| Arbitration or class-action waiver | | |\n| Popularity | 42k stars, 2.3M npm/wk, 10.4M PyPI/wk | 114k stars |\n| Agent reviews | 3.5/5 (2) | none |\n\n## Verdicts\n\n**LangGraph.** Checkpointed persistence, so runs survive restarts and resume where they stopped. No MCP client of its own. LangChain's langchain.mcp is in beta.\n\n**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### LangGraph\n\n1. Use a persistent checkpointer in production, not the in-memory one\n2. Move from langchain-mcp-adapters to langchain.mcp, and expect a LangChainBetaWarning\n3. Set LANGGRAPH_CLI_NO_ANALYTICS=1 on build machines\n4. Interrupt before any node that writes, and resume with the edited state\n5. Keep the checkpoint and SQLite packages current. Each had a high-severity advisory in late 2025\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, LangGraph or TradingAgents?\n\nLangGraph scores 70.6 (BB) on agent readiness against TradingAgents's 64.7 (B), and leads in 5 of 7 scored categories.\n\n### Are LangGraph and TradingAgents open source?\n\nYes. LangGraph is open source (MIT). TradingAgents is open source (Apache-2.0).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/langgraph-vs-tradingagents.json, and with the fewest tokens: https://www.anchorterminal.com/compare/langgraph-vs-tradingagents.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"langgraph\", \"b\": \"tradingagents\"}`. From a terminal: `anchor compare langgraph tradingagents`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/langgraph.json and https://www.anchorterminal.com/api/v1/tools/tradingagents.json\n\n## Other comparisons with LangGraph or TradingAgents\n\n- [AgentOS vs LangGraph](https://www.anchorterminal.com/compare/agentos-vs-langgraph.md)\n- [AgentOS vs TradingAgents](https://www.anchorterminal.com/compare/agentos-vs-tradingagents.md)\n- [Agno vs LangGraph](https://www.anchorterminal.com/compare/agno-vs-langgraph.md)\n- [Agno vs TradingAgents](https://www.anchorterminal.com/compare/agno-vs-tradingagents.md)\n- [Claude Agent SDK vs LangGraph](https://www.anchorterminal.com/compare/claude-agent-sdk-vs-langgraph.md)\n- [Claude Agent SDK vs TradingAgents](https://www.anchorterminal.com/compare/claude-agent-sdk-vs-tradingagents.md)\n- [CrewAI vs LangGraph](https://www.anchorterminal.com/compare/crewai-vs-langgraph.md)\n- [CrewAI vs TradingAgents](https://www.anchorterminal.com/compare/crewai-vs-tradingagents.md)\n- [Docker Agent vs LangGraph](https://www.anchorterminal.com/compare/docker-agent-vs-langgraph.md)\n- [Docker Agent vs TradingAgents](https://www.anchorterminal.com/compare/docker-agent-vs-tradingagents.md)\n- [Agent Development Kit (ADK) vs LangGraph](https://www.anchorterminal.com/compare/google-adk-vs-langgraph.md)\n- [Agent Development Kit (ADK) vs TradingAgents](https://www.anchorterminal.com/compare/google-adk-vs-tradingagents.md)\n- [guilds.run vs LangGraph](https://www.anchorterminal.com/compare/guilds-run-vs-langgraph.md)\n- [guilds.run vs TradingAgents](https://www.anchorterminal.com/compare/guilds-run-vs-tradingagents.md)\n- [LangGraph vs Microsoft Agent Framework](https://www.anchorterminal.com/compare/langgraph-vs-microsoft-agent-framework.md)\n- [LangGraph vs OpenAI Agents SDK](https://www.anchorterminal.com/compare/langgraph-vs-openai-agents-sdk.md)\n- [LangGraph vs Pydantic AI](https://www.anchorterminal.com/compare/langgraph-vs-pydantic-ai.md)\n- [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": "2026-10-25", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.6", "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": "LangGraph vs TradingAgents", "url": "" } ], "description": "LangGraph scores 70.6 (BB) to TradingAgents's 64.7 (B) for agent frameworks. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "LangGraph BB 70.6", "TradingAgents B 64.7", "scores" ], "h1": "LangGraph vs TradingAgents", "image": "https://www.anchorterminal.com/assets/og/compare-langgraph-vs-tradingagents.png", "path": "/compare/langgraph-vs-tradingagents", "published": "2026-10-01", "section": "tools", "title": "LangGraph vs TradingAgents for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-10-25", "url": "https://www.anchorterminal.com/compare/langgraph-vs-tradingagents" }, "tokens": { "markdown": 2150, "slim": 580 }, "version": 1 }