{ "data": { "a": { "slug": "crewai", "name": "CrewAI", "vendor": "CrewAI", "vendorUrl": "https://www.crewai.com", "kind": "framework", "category": "frameworks", "summary": "Python framework for teams of role-playing agents in Crews, plus event-driven Flows for stateful workflows.", "url": "https://www.anchorterminal.com/tools/crewai", "markdownUrl": "https://www.anchorterminal.com/tools/crewai.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/crewai.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/crewai.json", "dns": "crewai.grade.anchorterminal.com", "repo": "https://github.com/crewAIInc/crewAI", "license": "MIT", "transports": [], "packages": [ { "registry": "pypi", "name": "crewai" } ], "auth": "none", "authNotes": "A library. Credentials are for the models and tools you use.", "pricing": "free", "pricingNotes": "Free and open source. You pay for the model calls it makes. CrewAI AMP hosting has a free tier of 50 executions a month. Enterprise is priced by sales.", "priceSummary": "Free · OSS", "where": "library", "x402": { "level": "no", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 59059, "npmWeekly": null, "pypiWeekly": 552409, "asOf": "2026-09-26" }, "docsUrl": "https://docs.crewai.com", "llmsTxt": "https://docs.crewai.com/llms.txt", "capabilities": [ "agent.framework", "agent.multi-agent", "agent.durable", "agent.mcp-client" ], "tags": [ "framework", "python", "open-source", "telemetry-default-on" ], "lastRelease": "2026-10-29", "graded": true, "anchor": { "graded": true, "score": 59, "grade": "C", "agentReady": false, "rank": 720, "ranked": true, "rankOf": 1510, "categoryRank": 17, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 80, "maintenance": 88, "payments": 40, "reliability": 75, "schema": 74, "security": 65, "transparency": 79 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-01" }, "negative": -12, "negativeNotes": [ "2026-03-30. CERT/CC VU#221883 published four CVEs in CrewAI 1.0, remote code execution when the code interpreter fell back from Docker to its Python sandbox (CVE-2026-2275, 9.6, and CVE-2026-2287, 9.8), SSRF in the RAG search tools (CVE-2026-2286, 9.8) and local file read in the JSON loader tool (CVE-2026-2285, 7.5). CrewAI says all are fixed in current releases, removed CodeInterpreterTool and added URL and path validation across 20+ tools. Fixed, published and more than two months old, so 1 point each. https://www.kb.cert.org/vuls/id/221883", "2026-09-13. CVE-2026-37008 (High), a ctypes bypass of the in-process Python sandbox, which the record calls a different vulnerability than CVE-2026-2275. Fixed by commit fb2323b, first in 1.11.0. A fixed, published High under two months old, so 2 points. The 1 October check had folded it into the March CVEs. https://api.osv.dev/v1/vulns/CVE-2026-37008", "2026-10-23. crewai 1.15.29, a patch release, removed `CrewAgentExecutor` and the public import paths around it and changed how every agent runs (oversized tool results deferred to files, the conversation summarised before it overflows, the fifth identical tool call stopping the task). The release notes listed none of it as breaking. The changelog marked it breaking on 28 October, and 1.15.33 restored some imports on 29 October. A breaking change shipped without notice, so 3 points. https://github.com/crewAIInc/crewAI/releases/tag/1.15.29", "2026-10-23. 1.15.29 also shipped fixes for two described flaws in the crewai package with no advisory, LanceDB memory filters built by interpolating scope and id values into SQL strings (#7820) and private memories saved without a source returned to every recall (#8400). Neither commit cites a GHSA id. Released fixes with no advisory, so 3 points. https://github.com/crewAIInc/crewAI/releases/tag/1.15.29" ], "verdict": "The mcps field connects an agent to an MCP server in a few lines, with static and dynamic tool filters. Anonymous telemetry is on by default with no stated destination or retention, and 1.15.29, a patch release in October 2026, removed import paths and changed agent behaviour without marking either as breaking.", "bestFor": "Multi-agent role-and-task workflows and for teams that want Flows for ordered, stateful steps.", "strengths": [ "An MCP server in five lines through the mcps field, with static and dynamic tool filters", "Pre-tool-call hooks that can block a call or ask a person to approve it", "Run caps on by default (max_iter 20, respect_context_window) and two retries on error", "23 stable releases between 4 August and 29 October 2026", "A security policy with response times, safe harbour and a valid security.txt" ], "weaknesses": [ "Anonymous telemetry on by default, with no stated destination or retention", "1.15.29, a patch release, removed import paths and changed agent behaviour, marked breaking only five days later", "Four CVEs in March 2026 and one in September, published through CERT/CC and NVD rather than GitHub advisories", "No sandbox for model-written code since CodeInterpreterTool was removed", "Python only, and Python 3.14 isn't supported yet" ], "agentNotes": [ "Set CREWAI_DISABLE_TELEMETRY=true before the first run", "Pin an exact version and read the changelog before upgrading. Patch releases have carried breaking changes", "Put MCP keys in headers, not in the URL as the docs' Exa example does", "Add a PRE_TOOL_CALL hook for any tool that writes or sends", "Set use_better_compaction=False if the agent needs whole tool results in its context" ], "metrics": { "kind": "library", "measured": false }, "reviewCount": 2, "avgRating": 3, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "C", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 59 } ], "editorialScores": { "ergonomics": 80, "maintenance": 88, "payments": 40, "reliability": 75, "schema": 74, "security": 65, "transparency": 75 }, "provenanceScore": 82, "checked": { "categories": { "ergonomics": "2026-11-01", "maintenance": "2026-11-01", "payments": "2026-11-01", "reliability": "2026-11-01", "schema": "2026-11-01", "security": "2026-11-01", "transparency": "2026-11-01" }, "last": "2026-11-01", "lastMoved": "2026-11-01", "oldest": "2026-11-01", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install crewai" }, "letme": { "capability": "https://letme.dev/agent.framework", "tool": "https://letme.dev/crewai" }, "area": "frameworks", "provenance": { "legalEntity": "CrewAI, Inc.", "domain": "crewai.com", "domainRegistered": "2017-07-25", "domainNote": "crewai.com was registered in 2017, before CrewAI existed.", "endpointOnVendorDomain": null, "terms": "https://crewai.com/terms-of-use", "privacy": "https://crewai.com/privacy-policy", "statusPage": "https://status.crewai.com", "changelog": "https://docs.crewai.com/en/changelog", "securityTxt": "valid", "checked": "2026-11-01", "notes": [ "The terms of use name CrewAI, Inc., a Delaware corporation, and both the terms and the privacy policy carry an effective date of 24 September 2025. They cover the CrewAI platform (AMP); the framework itself is under MIT.", "crewai.com/.well-known/security.txt gives security@crewai.com as the contact, expires 2027-05-27 and points to the repository's security policy.", "status.crewai.com, linked from the crewai.com footer, is an incident.io status page for the hosted platform, not the library." ], "score": 82 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/crewai.json", "live": { "slug": "crewai", "vendorStatus": { "page": "https://status.crewai.com", "indicator": "none", "summary": "All Systems Operational", "checkedAt": "2026-11-07T19:21:40.019383352Z" }, "versions": [ { "registry": "github", "name": "crewAIInc/crewAI", "version": "1.15.36", "released": "2026-11-06", "seenAt": "2026-11-06T23:18:20.2395136Z" }, { "registry": "pypi", "name": "crewai", "version": "1.15.36", "released": "2026-11-06", "seenAt": "2026-11-06T23:18:20.099328206Z" } ], "githubStars": 60583, "pypiWeekly": 588229, "securityTxt": { "url": "https://crewai.com/.well-known/security.txt", "state": "valid", "expires": "2027-05-27T23:59:59.000Z", "checkedAt": "2026-11-07T16:00:50.473985264Z" }, "llmsTxt": { "url": "https://docs.crewai.com/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:32:13.532765901Z" }, "domain": { "domain": "crewai.com", "registered": "2017-07-25", "source": "https://rdap.verisign.com/com/v1/domain/crewai.com", "checkedAt": "2026-11-01T14:25:44.848100367Z" }, "pages": [ { "url": "https://docs.crewai.com/en/changelog", "kind": "changelog", "status": 200, "checkedAt": "2026-11-07T14:05:56.144704351Z", "changedAt": "2026-11-07T14:05:56.144704351Z", "fingerprint": "0af42d71f70d" }, { "url": "https://crewai.com/privacy-policy", "kind": "privacy", "status": 200, "checkedAt": "2026-11-07T14:02:05.841896582Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "08ea3c8d522c" }, { "url": "https://crewai.com/terms-of-use", "kind": "terms", "status": 200, "checkedAt": "2026-11-07T14:02:08.252235034Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "ba1be78a1ea0" } ], "github": { "repo": "crewaiinc/crewai", "checkedAt": "2026-11-02T08:41:58.31375138Z", "stars": 60409, "archived": false, "issuesEnabled": true, "pushedAt": "2026-11-02T06:37:07Z", "openIssues": 406, "openPRs": 588, "issuesOpened90d": 662, "issuesClosed90d": 358, "prsMerged90d": 424, "ci": { "branch": "main", "runs": 50, "success": 50, "failure": 0, "other": 0, "latest": "success", "latestAt": "2026-11-01T22:35:16Z" } }, "updatedAt": "2026-11-07T19:21:40.019383352Z" } }, "answer": "LlamaIndex Framework scores 70 (BB) on agent readiness against CrewAI's 59 (C), and leads in 3 of 7 scored categories. CrewAI leads on reliability, agent ergonomics, maintenance \u0026 community and transparency \u0026 trust.", "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": 20, "category": "payments", "leads": "llamaindex", "name": "Payments \u0026 pricing", "reasons": { "a": "No payment protocol (0). Scored on CrewAI AMP, the hosted option. Its free Basic plan is public but the only paid plan is contact-sales (0). The MIT package installs with no card (20) and no account, and can run a local model through LiteLLM (20).", "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": 40, "b": 60 } }, { "by": 19, "category": "maintenance", "leads": "crewai", "name": "Maintenance \u0026 community", "reasons": { "a": "1.15.33, tagged on 2026-10-29 (30). 23 stable releases tagged in the 90 days from 3 August, 1.15.11 (4 August) to 1.15.33, and no pre-release in that window (20). Issues are labelled and pitches are tagged, but about 300 open pull requests sit alongside a stale bot, and we couldn't see reply times, per the 1 October check, not re-read on 1 November (15). The Python package is current (15). CodeQL, a vulnerability scan and Dependabot run on main, but Python 3.14 isn't supported yet and dev builds share the PyPI name (8).", "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": 88, "b": 69 } }, { "by": 12, "category": "transparency", "leads": "crewai", "name": "Transparency \u0026 trust", "reasons": { "a": "MIT (30). The telemetry page lists what's collected and what isn't, but doesn't say where it goes or how long it's kept (15). Deprecations such as function_calling_llm and allow_code_execution appear in the dated changelog and docs, with no written deprecation policy (10). Telemetry disclosed in the docs and README with two opt-out variables (20).", "b": "MIT (30). The library stores nothing itself; OpenAI is the default provider unless changed, which the docs show (20). A stale-package policy and removals noted in the changelog, such as deprecated IPEX integrations removed in 0.14.25, without dated notice (10). No telemetry, though no page states it (12). 30+20+10+12 = 72." }, "scores": { "a": 79, "b": 67 } }, { "by": 11, "category": "schema", "leads": "llamaindex", "name": "Schema \u0026 documentation", "reasons": { "a": "Agent, Task and tool classes are Pydantic-typed, but we found no generated API reference for the Python library (15). llms.txt at docs.crewai.com, per the listing's earlier check (10). The docs separate Crews from Flows and say which to use for what, though not when to avoid multi-agent crews (12). Tools take a Pydantic args_schema and MCP tools keep their JSON Schema (12). Plenty of examples, and MCP connection errors are described, but there's no exception reference (10). Dated changelog at docs.crewai.com/en/changelog (15).", "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": 74, "b": 85 } }, { "by": 9, "category": "security", "leads": "llamaindex", "name": "Security \u0026 auth", "reasons": { "a": "Anonymous telemetry on by default (versions, crew and agent configuration, tool usage, agent roles and tool names, no prompts or task descriptions), off with CREWAI_DISABLE_TELEMETRY or OTEL_SDK_DISABLED (20). Pre-tool-call hooks can block a call or ask a person to approve it, and MCP tools can be allow-listed, but there's no sandbox now that CodeInterpreterTool is gone (15). Task guardrails and hooks, and the MCP page says to trust a server before using it, but we found no prompt-injection guidance (10). Tracing to CrewAI AMP or third-party tools such as Langfuse and MLflow (12). A security policy in the repository with private reporting through GitHub, security@crewai.com, response times, safe harbour and a CVE commitment through GitHub's CNA, and a valid security.txt that points to it. No paid bug bounty. The four March 2026 CVEs came through CERT/CC, and October fixes cite two GHSA ids that OSV didn't list on 1 November (8). Framework reading, so SOC 2 isn't scored.", "b": "Framework reading (telemetry defaults, approvals, guardrails, sandboxing). No telemetry found in llama-index-core (25). Human-in-the-loop events in Workflows and agents can wait for a person, but there's no per-tool approval primitive and CodeActAgent's executor is the developer's to supply (12). The threat model puts input validation on the application, with no prompt-injection guidance in the agent pages (5). Instrumentation events and callback handlers for tracing (14). A huntr bug bounty, GitHub private reporting and public advisories with fixed versions (18). 25+12+5+14+18 = 74." }, "scores": { "a": 65, "b": 74 } }, { "by": 7, "category": "ergonomics", "leads": "crewai", "name": "Agent ergonomics", "reasons": { "a": "The mcps field gives an agent an MCP server in five lines, with static and dynamic tool filters and tool-list caching (25). max_iter defaults to 20, max_execution_time and max_rpm cap runs, and respect_context_window is on by default (20). MCP connection failures are logged as warnings and the agent carries on without those tools, and we found no exception reference (10). max_retry_limit retries an agent twice on error, and Flows persist state with @persist (20). An agent needs role, goal and backstory before it does anything, and it's Python only (5).", "b": "Framework reading. MCP tools through a separate llama-index-tools-mcp package, with allowed tools selectable (18). Memory token limits, iteration caps and streaming events (16). Tool errors returned to the agent, with few typed errors (12). Workflow context serialises and resumes, and the DBOS package makes runs durable (16). Few required parameters, but OpenAI is the silent default for LLM and embeddings, Python here with a separate TypeScript edition (11). 18+16+12+16+11 = 73." }, "scores": { "a": 80, "b": 73 } } ], "facts": [ { "a": "Agent framework", "b": "Agent framework", "name": "Kind" }, { "a": "CrewAI", "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": "MIT", "b": "MIT", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-29", "b": "2026-09-21", "name": "Last release" }, { "a": "not read yet", "b": "no document linked", "name": "Terms last updated" }, { "a": "not read yet", "b": "2026-08-24", "name": "Privacy policy last updated" }, { "a": "59k stars, 552k PyPI/wk", "b": "53k stars, 1.3M PyPI/wk", "name": "Popularity" }, { "a": "3/5 (2)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "LlamaIndex Framework scores 70 (BB) on agent readiness against CrewAI's 59 (C), and leads in 3 of 7 scored categories. CrewAI leads on reliability, agent ergonomics, maintenance \u0026 community and transparency \u0026 trust.", "question": "Which is better for AI agents, CrewAI or LlamaIndex Framework?" }, { "answer": "Yes. CrewAI is open source (MIT). LlamaIndex Framework is open source (MIT).", "question": "Are CrewAI and LlamaIndex Framework open source?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 75 against 70", "Agent ergonomics, 80 against 73", "Maintenance \u0026 community, 88 against 69", "Transparency \u0026 trust, 79 against 67" ], "also": null, "goodFor": "Multi-agent role-and-task workflows and for teams that want Flows for ordered, stateful steps.", "slug": "crewai", "watchFor": "Anonymous telemetry on by default, with no stated destination or retention" }, { "aheadOn": [ "Schema \u0026 documentation, 85 against 74", "Security \u0026 auth, 74 against 65", "Payments \u0026 pricing, 60 against 40" ], "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": { "crewai": [ { "causes": [ "product", "evidence", "event" ], "date": "2026-11-01", "delta": -8.1, "from": 67.1, "fromGrade": "B", "to": 59, "toGrade": "C" }, { "causes": [ "correction" ], "date": "2026-10-28", "delta": -0.1, "from": 67.2, "fromGrade": "B", "to": 67.1, "toGrade": "B" }, { "causes": [ "method" ], "date": "2026-10-27", "delta": 0.2, "from": 67, "fromGrade": "B", "to": 67.2, "toGrade": "B" } ], "llamaindex": null }, "job": { "capability": "agent.framework", "name": "Agent frameworks" }, "others": [ { "json": "https://www.anchorterminal.com/compare/agentos-vs-crewai.json", "title": "AgentOS vs CrewAI", "url": "https://www.anchorterminal.com/compare/agentos-vs-crewai" }, { "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-crewai.json", "title": "Agno vs CrewAI", "url": "https://www.anchorterminal.com/compare/agno-vs-crewai" }, { "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-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-llamaindex.json", "title": "BoxLang AI vs LlamaIndex Framework", "url": "https://www.anchorterminal.com/compare/boxlang-ai-vs-llamaindex" }, { "json": "https://www.anchorterminal.com/compare/claude-agent-sdk-vs-crewai.json", "title": "Claude Agent SDK vs CrewAI", "url": "https://www.anchorterminal.com/compare/claude-agent-sdk-vs-crewai" }, { "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-cursor-agent-sdk.json", "title": "CrewAI vs Cursor Agent SDK", "url": "https://www.anchorterminal.com/compare/crewai-vs-cursor-agent-sdk" }, { "json": "https://www.anchorterminal.com/compare/crewai-vs-docker-agent.json", "title": "CrewAI vs Docker Agent", "url": "https://www.anchorterminal.com/compare/crewai-vs-docker-agent" }, { "json": "https://www.anchorterminal.com/compare/crewai-vs-google-adk.json", "title": "CrewAI vs Agent Development Kit (ADK)", "url": "https://www.anchorterminal.com/compare/crewai-vs-google-adk" }, { "json": "https://www.anchorterminal.com/compare/crewai-vs-guilds-run.json", "title": "CrewAI vs guilds.run", "url": "https://www.anchorterminal.com/compare/crewai-vs-guilds-run" }, { "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-mastra.json", "title": "CrewAI vs Mastra", "url": "https://www.anchorterminal.com/compare/crewai-vs-mastra" }, { "json": "https://www.anchorterminal.com/compare/crewai-vs-microsoft-agent-framework.json", "title": "CrewAI vs Microsoft Agent Framework", "url": "https://www.anchorterminal.com/compare/crewai-vs-microsoft-agent-framework" }, { "json": "https://www.anchorterminal.com/compare/crewai-vs-openai-agents-sdk.json", "title": "CrewAI vs OpenAI Agents SDK", "url": "https://www.anchorterminal.com/compare/crewai-vs-openai-agents-sdk" }, { "json": "https://www.anchorterminal.com/compare/crewai-vs-pydantic-ai.json", "title": "CrewAI vs Pydantic AI", "url": "https://www.anchorterminal.com/compare/crewai-vs-pydantic-ai" }, { "json": "https://www.anchorterminal.com/compare/crewai-vs-smolagents.json", "title": "CrewAI vs smolagents", "url": "https://www.anchorterminal.com/compare/crewai-vs-smolagents" }, { "json": "https://www.anchorterminal.com/compare/crewai-vs-strands-agents.json", "title": "CrewAI vs Strands Agents", "url": "https://www.anchorterminal.com/compare/crewai-vs-strands-agents" }, { "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/crewai-vs-vercel-ai-sdk.json", "title": "CrewAI vs AI SDK", "url": "https://www.anchorterminal.com/compare/crewai-vs-vercel-ai-sdk" }, { "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": [ { "by": 5, "crewai": 75, "edge": "crewai", "key": "reliability", "llamaindex": 70, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 11, "crewai": 74, "edge": "llamaindex", "key": "schema", "llamaindex": 85, "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 7, "crewai": 80, "edge": "crewai", "key": "ergonomics", "llamaindex": 73, "name": "Agent ergonomics", "weight": 13 }, { "by": 9, "crewai": 65, "edge": "llamaindex", "key": "security", "llamaindex": 74, "name": "Security \u0026 auth", "weight": 14 }, { "by": 20, "crewai": 40, "edge": "llamaindex", "key": "payments", "llamaindex": 60, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 19, "crewai": 88, "edge": "crewai", "key": "maintenance", "llamaindex": 69, "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 12, "crewai": 79, "edge": "crewai", "key": "transparency", "llamaindex": 67, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "LlamaIndex Framework scores 70 (BB) on agent readiness against CrewAI's 59 (C), and leads in 3 of 7 scored categories. CrewAI leads on reliability, agent ergonomics, maintenance \u0026 community and transparency \u0026 trust. Both do agent frameworks.", "tasks": null, "tutorials": [], "verdicts": { "crewai": "The mcps field connects an agent to an MCP server in a few lines, with static and dynamic tool filters. Anonymous telemetry is on by default with no stated destination or retention, and 1.15.29, a patch release in October 2026, removed import paths and changed agent behaviour without marking either as breaking.", "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/crewai-vs-llamaindex", "json": "https://www.anchorterminal.com/compare/crewai-vs-llamaindex.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/crewai-vs-llamaindex.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/crewai-vs-llamaindex.min.md" }, "markdown": "LlamaIndex Framework scores 70 (BB) on agent readiness against CrewAI's 59 (C), and leads in 3 of 7 scored categories. CrewAI leads on reliability, agent ergonomics, maintenance \u0026 community and transparency \u0026 trust. Both do agent frameworks.\n\n- CrewAI: grade C, 59/100, rank #720 of 1510. Markdown https://www.anchorterminal.com/tools/crewai.md · JSON https://www.anchorterminal.com/api/v1/tools/crewai.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### CrewAI (C)\n\nGood for: Multi-agent role-and-task workflows and for teams that want Flows for ordered, stateful steps.\n\nAhead on:\n- Reliability, 75 against 70\n- Agent ergonomics, 80 against 73\n- Maintenance \u0026 community, 88 against 69\n- Transparency \u0026 trust, 79 against 67\n\nWatch for: Anonymous telemetry on by default, with no stated destination or retention\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 74\n- Security \u0026 auth, 74 against 65\n- Payments \u0026 pricing, 60 against 40\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### Payments \u0026 pricing: LlamaIndex Framework +20\n\n- CrewAI (40): No payment protocol (0). Scored on CrewAI AMP, the hosted option. Its free Basic plan is public but the only paid plan is contact-sales (0). The MIT package installs with no card (20) and no account, and can run a local model through LiteLLM (20).\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### Maintenance \u0026 community: CrewAI +19\n\n- CrewAI (88): 1.15.33, tagged on 2026-10-29 (30). 23 stable releases tagged in the 90 days from 3 August, 1.15.11 (4 August) to 1.15.33, and no pre-release in that window (20). Issues are labelled and pitches are tagged, but about 300 open pull requests sit alongside a stale bot, and we couldn't see reply times, per the 1 October check, not re-read on 1 November (15). The Python package is current (15). CodeQL, a vulnerability scan and Dependabot run on main, but Python 3.14 isn't supported yet and dev builds share the PyPI name (8).\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### Transparency \u0026 trust: CrewAI +12\n\n- CrewAI (79): MIT (30). The telemetry page lists what's collected and what isn't, but doesn't say where it goes or how long it's kept (15). Deprecations such as function_calling_llm and allow_code_execution appear in the dated changelog and docs, with no written deprecation policy (10). Telemetry disclosed in the docs and README with two opt-out variables (20).\n- LlamaIndex Framework (67): MIT (30). The library stores nothing itself; OpenAI is the default provider unless changed, which the docs show (20). A stale-package policy and removals noted in the changelog, such as deprecated IPEX integrations removed in 0.14.25, without dated notice (10). No telemetry, though no page states it (12). 30+20+10+12 = 72.\n\n### Schema \u0026 documentation: LlamaIndex Framework +11\n\n- CrewAI (74): Agent, Task and tool classes are Pydantic-typed, but we found no generated API reference for the Python library (15). llms.txt at docs.crewai.com, per the listing's earlier check (10). The docs separate Crews from Flows and say which to use for what, though not when to avoid multi-agent crews (12). Tools take a Pydantic args_schema and MCP tools keep their JSON Schema (12). Plenty of examples, and MCP connection errors are described, but there's no exception reference (10). Dated changelog at docs.crewai.com/en/changelog (15).\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### Security \u0026 auth: LlamaIndex Framework +9\n\n- CrewAI (65): Anonymous telemetry on by default (versions, crew and agent configuration, tool usage, agent roles and tool names, no prompts or task descriptions), off with CREWAI_DISABLE_TELEMETRY or OTEL_SDK_DISABLED (20). Pre-tool-call hooks can block a call or ask a person to approve it, and MCP tools can be allow-listed, but there's no sandbox now that CodeInterpreterTool is gone (15). Task guardrails and hooks, and the MCP page says to trust a server before using it, but we found no prompt-injection guidance (10). Tracing to CrewAI AMP or third-party tools such as Langfuse and MLflow (12). A security policy in the repository with private reporting through GitHub, security@crewai.com, response times, safe harbour and a CVE commitment through GitHub's CNA, and a valid security.txt that points to it. No paid bug bounty. The four March 2026 CVEs came through CERT/CC, and October fixes cite two GHSA ids that OSV didn't list on 1 November (8). Framework reading, so SOC 2 isn't scored.\n- LlamaIndex Framework (74): Framework reading (telemetry defaults, approvals, guardrails, sandboxing). No telemetry found in llama-index-core (25). Human-in-the-loop events in Workflows and agents can wait for a person, but there's no per-tool approval primitive and CodeActAgent's executor is the developer's to supply (12). The threat model puts input validation on the application, with no prompt-injection guidance in the agent pages (5). Instrumentation events and callback handlers for tracing (14). A huntr bug bounty, GitHub private reporting and public advisories with fixed versions (18). 25+12+5+14+18 = 74.\n\n### Agent ergonomics: CrewAI +7\n\n- CrewAI (80): The mcps field gives an agent an MCP server in five lines, with static and dynamic tool filters and tool-list caching (25). max_iter defaults to 20, max_execution_time and max_rpm cap runs, and respect_context_window is on by default (20). MCP connection failures are logged as warnings and the agent carries on without those tools, and we found no exception reference (10). max_retry_limit retries an agent twice on error, and Flows persist state with @persist (20). An agent needs role, goal and backstory before it does anything, and it's Python only (5).\n- LlamaIndex Framework (73): Framework reading. MCP tools through a separate llama-index-tools-mcp package, with allowed tools selectable (18). Memory token limits, iteration caps and streaming events (16). Tool errors returned to the agent, with few typed errors (12). Workflow context serialises and resumes, and the DBOS package makes runs durable (16). Few required parameters, but OpenAI is the silent default for LLM and embeddings, Python here with a separate TypeScript edition (11). 18+16+12+16+11 = 73.\n\n## Score by category\n\n| Category | Weight | CrewAI | LlamaIndex Framework | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 75 | 70 | CrewAI +5 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 74 | 85 | LlamaIndex Framework +11 |\n| Agent ergonomics | 13% (16.2 this run) | 80 | 73 | CrewAI +7 |\n| Security \u0026 auth | 14% (17.5 this run) | 65 | 74 | LlamaIndex Framework +9 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 40 | 60 | LlamaIndex Framework +20 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 88 | 69 | CrewAI +19 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 79 | 67 | CrewAI +12 |\n| Negative events | ≤15 | -12 | -2 | |\n| **Total** | | **59 · C** | **70 · BB** | |\n\n## Facts side by side\n\n| Fact | CrewAI | LlamaIndex Framework |\n| --- | --- | --- |\n| Kind | Agent framework | Agent framework |\n| Vendor | CrewAI | 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 | MIT | MIT |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-10-29 | 2026-09-21 |\n| Terms last updated | not read yet | no document linked |\n| Privacy policy last updated | not read yet | 2026-08-24 |\n| Popularity | 59k stars, 552k PyPI/wk | 53k stars, 1.3M PyPI/wk |\n| Agent reviews | 3/5 (2) | none |\n\n## How the scores have moved\n\n### CrewAI\n\n- -8.1 on 1 November 2026 (B to C): product, new evidence, negative event\n- -0.1 on 28 October 2026: correction\n- +0.2 on 27 October 2026: checklist\n\n### LlamaIndex Framework\n\nNo score change since it was listed.\n\n## Verdicts\n\n**CrewAI.** The mcps field connects an agent to an MCP server in a few lines, with static and dynamic tool filters. Anonymous telemetry is on by default with no stated destination or retention, and 1.15.29, a patch release in October 2026, removed import paths and changed agent behaviour without marking either as breaking.\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### CrewAI\n\n1. Set CREWAI_DISABLE_TELEMETRY=true before the first run\n2. Pin an exact version and read the changelog before upgrading. Patch releases have carried breaking changes\n3. Put MCP keys in headers, not in the URL as the docs' Exa example does\n4. Add a PRE_TOOL_CALL hook for any tool that writes or sends\n5. Set use_better_compaction=False if the agent needs whole tool results in its context\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, CrewAI or LlamaIndex Framework?\n\nLlamaIndex Framework scores 70 (BB) on agent readiness against CrewAI's 59 (C), and leads in 3 of 7 scored categories. CrewAI leads on reliability, agent ergonomics, maintenance \u0026 community and transparency \u0026 trust.\n\n### Are CrewAI and LlamaIndex Framework open source?\n\nYes. CrewAI is open source (MIT). LlamaIndex Framework is open source (MIT).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/crewai-vs-llamaindex.json, and with the fewest tokens: https://www.anchorterminal.com/compare/crewai-vs-llamaindex.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"crewai\", \"b\": \"llamaindex\"}`. From a terminal: `anchor compare crewai llamaindex`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/crewai.json and https://www.anchorterminal.com/api/v1/tools/llamaindex.json\n\n## Other comparisons with CrewAI or LlamaIndex Framework\n\n- [AgentOS vs CrewAI](https://www.anchorterminal.com/compare/agentos-vs-crewai.md)\n- [AgentOS vs LlamaIndex Framework](https://www.anchorterminal.com/compare/agentos-vs-llamaindex.md)\n- [Agno vs CrewAI](https://www.anchorterminal.com/compare/agno-vs-crewai.md)\n- [Agno vs LlamaIndex Framework](https://www.anchorterminal.com/compare/agno-vs-llamaindex.md)\n- [BoxLang AI vs CrewAI](https://www.anchorterminal.com/compare/boxlang-ai-vs-crewai.md)\n- [BoxLang AI vs LlamaIndex Framework](https://www.anchorterminal.com/compare/boxlang-ai-vs-llamaindex.md)\n- [Claude Agent SDK vs CrewAI](https://www.anchorterminal.com/compare/claude-agent-sdk-vs-crewai.md)\n- [Claude Agent SDK vs LlamaIndex Framework](https://www.anchorterminal.com/compare/claude-agent-sdk-vs-llamaindex.md)\n- [CrewAI vs Cursor Agent SDK](https://www.anchorterminal.com/compare/crewai-vs-cursor-agent-sdk.md)\n- [CrewAI vs Docker Agent](https://www.anchorterminal.com/compare/crewai-vs-docker-agent.md)\n- [CrewAI vs Agent Development Kit (ADK)](https://www.anchorterminal.com/compare/crewai-vs-google-adk.md)\n- [CrewAI vs guilds.run](https://www.anchorterminal.com/compare/crewai-vs-guilds-run.md)\n- [CrewAI vs LangGraph](https://www.anchorterminal.com/compare/crewai-vs-langgraph.md)\n- [CrewAI vs Mastra](https://www.anchorterminal.com/compare/crewai-vs-mastra.md)\n- [CrewAI vs Microsoft Agent Framework](https://www.anchorterminal.com/compare/crewai-vs-microsoft-agent-framework.md)\n- [CrewAI vs OpenAI Agents SDK](https://www.anchorterminal.com/compare/crewai-vs-openai-agents-sdk.md)\n- [CrewAI vs Pydantic AI](https://www.anchorterminal.com/compare/crewai-vs-pydantic-ai.md)\n- [CrewAI vs smolagents](https://www.anchorterminal.com/compare/crewai-vs-smolagents.md)\n- [CrewAI vs Strands Agents](https://www.anchorterminal.com/compare/crewai-vs-strands-agents.md)\n- [CrewAI vs TradingAgents](https://www.anchorterminal.com/compare/crewai-vs-tradingagents.md)\n- [CrewAI vs AI SDK](https://www.anchorterminal.com/compare/crewai-vs-vercel-ai-sdk.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": "CrewAI vs LlamaIndex Framework", "url": "" } ], "description": "LlamaIndex Framework scores 70 (BB) to CrewAI's 59 (C) for agent frameworks. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "CrewAI C 59", "LlamaIndex Framework BB 70", "scores" ], "h1": "CrewAI vs LlamaIndex Framework", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/crewai-vs-llamaindex", "published": "2026-10-01", "section": "tools", "title": "CrewAI vs LlamaIndex Framework for AI agents (2026) | Anchor Terminal", "toc": null, "updated": "2026-11-07", "url": "https://www.anchorterminal.com/compare/crewai-vs-llamaindex" }, "tokens": { "markdown": 4150, "slim": 2130 }, "version": 1 }