{
  "data": {
    "a": {
      "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"
      }
    },
    "answer": "LlamaIndex Framework scores 70 (BB) on agent readiness against smolagents's 58.7 (C), and leads in 6 of 7 scored categories.",
    "b": {
      "slug": "smolagents",
      "name": "smolagents",
      "vendor": "Hugging Face",
      "vendorUrl": "https://github.com/huggingface/smolagents",
      "kind": "framework",
      "category": "frameworks",
      "summary": "smolagents is Hugging Face's small Python library for agents that write and run Python code (CodeAgent) or call tools as JSON (ToolCallingAgent), with MCP tools, any model provider and sandboxed execution through E2B, Docker, Modal or Blaxel.",
      "url": "https://www.anchorterminal.com/tools/smolagents",
      "markdownUrl": "https://www.anchorterminal.com/tools/smolagents.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/smolagents.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/smolagents.json",
      "dns": "smolagents.grade.anchorterminal.com",
      "repo": "https://github.com/huggingface/smolagents",
      "license": "Apache-2.0",
      "transports": [],
      "packages": [
        {
          "registry": "pypi",
          "name": "smolagents"
        }
      ],
      "auth": "none",
      "authNotes": "A library with no credentials of its own. The default InferenceClientModel uses a Hugging Face token; other providers and remote sandboxes take their own keys.",
      "pricing": "free",
      "pricingNotes": "Free and open source under Apache-2.0. You pay for model calls and for any remote sandbox (E2B, Modal, Blaxel) you use.",
      "priceSummary": "Free · OSS",
      "where": "library",
      "x402": {
        "level": "no",
        "evidence": "No x402, MPP or L402 in the docs or the repository (checked 2026-11-06).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": 30234,
        "npmWeekly": null,
        "pypiWeekly": 171063,
        "asOf": "2026-11-06"
      },
      "docsUrl": "https://huggingface.co/docs/smolagents/index",
      "llmsTxt": "https://huggingface.co/docs/smolagents/llms.txt",
      "capabilities": [
        "agent.framework",
        "agent.mcp-client",
        "agent.multi-agent"
      ],
      "tags": [
        "framework",
        "python",
        "open-source",
        "llms-txt",
        "mcp",
        "code-agent",
        "sandbox"
      ],
      "lastRelease": "2026-05-29",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 58.7,
        "grade": "C",
        "agentReady": false,
        "rank": 739,
        "ranked": true,
        "rankOf": 1510,
        "categoryRank": 18,
        "methodology": "0.7",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 68,
          "maintenance": 34,
          "payments": 60,
          "reliability": 64,
          "schema": 81,
          "security": 66,
          "transparency": 65
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-11-06"
        },
        "negative": -6,
        "negativeNotes": [
          "2025-12-23 to 2026-03-27. GHSA-q9r5-6hrr-9ph7 (CVE-2025-14931, critical, from the Zero Day Initiative) reports remote code execution through pickle deserialisation in the remote Python executor; the fix for remote executors merged on 15 February 2026, about eight weeks after publication. CVE-2026-2654 (SSRF, 1.24.0) and CVE-2026-4963 (code injection in LocalPythonExecutor, an incomplete earlier fix) are rated low, and both records say the vendor did not respond. Fixed or low, under 12 months old, 6 points. https://osv.dev/vulnerability/GHSA-q9r5-6hrr-9ph7"
        ],
        "verdict": "A compact Python library for code-writing and tool-calling agents, with MCP tools, any model provider and remote sandboxes through E2B, Docker, Modal or Blaxel. The newest release is 1.26.0 of 29 May 2026, a critical remote-executor RCE took about eight weeks to fix, and the local executor isn't a security boundary.",
        "bestFor": "Small Python projects and research that want code-writing agents with minimal abstraction.",
        "strengths": [
          "CodeAgent and ToolCallingAgent in a small, readable codebase",
          "MCP tools from any server through MCPClient",
          "Remote execution through E2B, Docker, Modal or Blaxel, with a guide on when it's needed",
          "No telemetry found in the source",
          "llms.txt and Markdown docs on huggingface.co"
        ],
        "weaknesses": [
          "No release since 1.26.0 on 29 May 2026, and few commits to main since August",
          "The local Python executor isn't a security boundary, per its own guide",
          "A critical RCE in the remote executor (published December 2025) was fixed in February 2026",
          "No human approval hook, retry or resume built in",
          "Breaking removals such as WasmExecutor shipped in minor releases"
        ],
        "agentNotes": [
          "Run CodeAgent with `executor_type` set to e2b, docker, modal or blaxel whenever the model or its inputs aren't trusted",
          "Use smolagents 1.24.0 or later to get the remote-executor deserialisation fix",
          "Set max_steps and final_answer_checks so a run stops on its own",
          "Pass structured_output explicitly to MCPClient to avoid the default-change warning",
          "Pin the version, since minor releases have removed APIs"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 0,
        "avgRating": 0,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "C",
            "methodology": "0.7",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 58.7
          }
        ],
        "editorialScores": {
          "ergonomics": 68,
          "maintenance": 34,
          "payments": 60,
          "reliability": 64,
          "schema": 81,
          "security": 66,
          "transparency": 67
        },
        "provenanceScore": 62,
        "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 smolagents   # MCP: pip install 'smolagents[mcp]'"
      },
      "letme": {
        "capability": "https://letme.dev/agent.framework",
        "tool": "https://letme.dev/smolagents"
      },
      "sameCompany": [
        "hugging-face-inference-providers",
        "hugging-face-inference-endpoints",
        "carbon-x",
        "smollm3-3b"
      ],
      "area": "frameworks",
      "provenance": {
        "legalEntity": "Hugging Face, Inc.",
        "domain": "huggingface.co",
        "domainRegistered": "",
        "endpointOnVendorDomain": null,
        "terms": "https://huggingface.co/terms-of-service",
        "privacy": "https://huggingface.co/privacy",
        "statusPage": "",
        "changelog": "https://github.com/huggingface/smolagents/releases",
        "securityTxt": "unknown",
        "checked": "2026-11-06",
        "notes": [
          "SECURITY.md takes reports through GitHub private vulnerability reporting or security@huggingface.co, with no bounty.",
          "huggingface.co/robots.txt allows all crawlers.",
          "The terms and privacy links are Hugging Face's site-wide documents; the library itself collects nothing."
        ],
        "score": 62
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/smolagents.json",
      "live": {
        "slug": "smolagents",
        "versions": [
          {
            "registry": "github",
            "name": "huggingface/smolagents",
            "version": "v1.26.0",
            "released": "2026-05-29",
            "seenAt": "2026-11-07T00:06:55.865567193Z"
          },
          {
            "registry": "pypi",
            "name": "smolagents",
            "version": "1.26.0",
            "released": "2026-05-29",
            "seenAt": "2026-11-07T00:06:55.546186347Z"
          }
        ],
        "githubStars": 30238,
        "pypiWeekly": 171063,
        "securityTxt": {
          "url": "https://huggingface.co/.well-known/security.txt",
          "state": "valid",
          "expires": "2030-07-01T08:42:00.000Z",
          "checkedAt": "2026-11-07T16:00:00.493446773Z"
        },
        "llmsTxt": {
          "url": "https://huggingface.co/docs/smolagents/llms.txt",
          "ok": true,
          "status": 200,
          "checkedAt": "2026-11-07T15:33:57.593545427Z"
        },
        "updatedAt": "2026-11-07T16:00:00.493446773Z"
      }
    },
    "edges": [
      {
        "by": 35,
        "category": "maintenance",
        "leads": "llamaindex",
        "name": "Maintenance \u0026 community",
        "reasons": {
          "a": "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.",
          "b": "v1.26.0 on 29 May 2026, 161 days before this check (10). No release in the 90 days to 6 November (0). 416 open issues and 1,045 open issues and pull requests on 6 November, with 144 issues opened in the 90 days to 3 November. Of the 50 newest, 26 had a comment and 1 was closed. Two 2026 CVE records say the vendor didn't respond to the reporter, and seven commits reached main from 8 August to 6 November (6). Python only, and the package is the current one (10). CI with actions pinned to commit SHAs and Dependabot for actions (8). 10+0+6+10+8 = 34."
        },
        "scores": {
          "a": 69,
          "b": 34
        }
      },
      {
        "by": 8,
        "category": "security",
        "leads": "llamaindex",
        "name": "Security \u0026 auth",
        "reasons": {
          "a": "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.",
          "b": "Framework reading (telemetry defaults, approvals, guardrails, sandboxing). No telemetry found in the source (25). No human approval hook beyond step callbacks; the local executor restricts imports but the guide says it isn't a security tool, and isolation needs a remote executor (10). The secure execution guide covers LLM-generated code risks, without prompt-injection guidance for tool output (7). OpenTelemetry tracing through OpenInference and run inspection (12). SECURITY.md with private reporting and CVE credit, and the remote-executor RCE was fixed in public, but two 2026 CVE records say the vendor didn't respond (12). 25+10+7+12+12 = 66."
        },
        "scores": {
          "a": 74,
          "b": 66
        }
      },
      {
        "by": 6,
        "category": "reliability",
        "leads": "llamaindex",
        "name": "Reliability",
        "reasons": {
          "a": "Local-package reading. Official PyPI packages with Python 3.10 to below 4.0 (20). Public unit-test, type-check, lint, coverage and CodeQL workflows, with the type-check, lint and CodeQL runs on main passing on 3 November (25). 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). A dated, generated changelog per package, but core is 0.x and minors such as 0.13 and 0.14 carried breaking changes (8). Core isn't 1.0; Workflows is at 2.x, so partial (5). 20+25+12+8+5 = 70.",
          "b": "Local-package reading. Official PyPI package with Python 3.10 or newer (20). A public tests workflow runs pytest on Python 3.10 and 3.12 for pushes and pull requests; whether main passes wasn't read (15). 416 open issues and 1,045 open issues and pull requests on 6 November, with 144 issues opened in the 90 days to 3 November. Of the 50 newest, 26 had a comment and 1 was closed. Two 2026 CVE records say the vendor didn't respond to the reporter, and seven commits reached main from 8 August to 6 November (6). Release notes on GitHub tags but no changelog file, and the remote WasmExecutor was removed in a minor release (8). 1.0 since 31 December 2024 (15). 20+15+6+8+15 = 64."
        },
        "scores": {
          "a": 70,
          "b": 64
        }
      },
      {
        "by": 5,
        "category": "ergonomics",
        "leads": "llamaindex",
        "name": "Agent ergonomics",
        "reasons": {
          "a": "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.",
          "b": "Framework reading. MCPClient loads an MCP server's tools in a few lines (20). max_steps, planning intervals and final_answer_checks bound a run (16). Errors from tools and code go back to the model as observations (14). No built-in retry, idempotency or resume beyond replaying memory (8). Few required parameters and many providers, Python only, and the default model needs a Hugging Face token (10). 20+16+14+8+10 = 68."
        },
        "scores": {
          "a": 73,
          "b": 68
        }
      }
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    "facts": [
      {
        "a": "Agent framework",
        "b": "Agent framework",
        "name": "Kind"
      },
      {
        "a": "LlamaIndex",
        "b": "Hugging Face",
        "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": "Apache-2.0",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "yes",
        "b": "yes",
        "name": "llms.txt"
      },
      {
        "a": "2026-09-21",
        "b": "2026-05-29",
        "name": "Last release"
      },
      {
        "a": "no document linked",
        "b": "2022-09-15",
        "name": "Terms last updated"
      },
      {
        "a": "2026-08-24",
        "b": "2023-03-28",
        "name": "Privacy policy last updated"
      },
      {
        "a": "not read yet",
        "b": "not found in the text",
        "name": "Customer content may train models"
      },
      {
        "a": "not read yet",
        "b": "not found in the text",
        "name": "Terms restrict automated access"
      },
      {
        "a": "not read yet",
        "b": "not found in the text",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "not read yet",
        "b": "yes",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "not read yet",
        "b": "not found in the text",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "53k stars, 1.3M PyPI/wk",
        "b": "30k stars, 171k PyPI/wk",
        "name": "Popularity"
      }
    ],
    "faq": [
      {
        "answer": "LlamaIndex Framework scores 70 (BB) on agent readiness against smolagents's 58.7 (C), and leads in 6 of 7 scored categories.",
        "question": "Which is better for AI agents, LlamaIndex Framework or smolagents?"
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      {
        "answer": "Yes. LlamaIndex Framework is open source (MIT). smolagents is open source (Apache-2.0).",
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        "aheadOn": null,
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        "slug": "smolagents",
        "watchFor": "No release since 1.26.0 on 29 May 2026, and few commits to main since August"
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        "key": "reliability",
        "llamaindex": 70,
        "name": "Reliability",
        "smolagents": 64,
        "weight": 16
      },
      {
        "key": "performance",
        "name": "Performance",
        "pending": true,
        "weight": 10
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        "edge": "llamaindex",
        "key": "schema",
        "llamaindex": 85,
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        "smolagents": 81,
        "weight": 13
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        "llamaindex": 73,
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        "smolagents": 68,
        "weight": 13
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        "edge": "llamaindex",
        "key": "security",
        "llamaindex": 74,
        "name": "Security \u0026 auth",
        "smolagents": 66,
        "weight": 14
      },
      {
        "by": 0,
        "edge": "",
        "key": "payments",
        "llamaindex": 60,
        "name": "Payments \u0026 pricing",
        "smolagents": 60,
        "weight": 10
      },
      {
        "key": "tasks",
        "name": "Task success",
        "pending": true,
        "weight": 10
      },
      {
        "by": 35,
        "edge": "llamaindex",
        "key": "maintenance",
        "llamaindex": 69,
        "name": "Maintenance \u0026 community",
        "smolagents": 34,
        "weight": 7
      },
      {
        "by": 2,
        "edge": "llamaindex",
        "key": "transparency",
        "llamaindex": 67,
        "name": "Transparency \u0026 trust",
        "smolagents": 65,
        "weight": 7
      }
    ],
    "summary": "LlamaIndex Framework scores 70 (BB) on agent readiness against smolagents's 58.7 (C), and leads in 6 of 7 scored categories. Both do agent frameworks.",
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    "verdicts": {
      "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.",
      "smolagents": "A compact Python library for code-writing and tool-calling agents, with MCP tools, any model provider and remote sandboxes through E2B, Docker, Modal or Blaxel. The newest release is 1.26.0 of 29 May 2026, a critical remote-executor RCE took about eight weeks to fix, and the local executor isn't a security boundary."
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  "markdown": "LlamaIndex Framework scores 70 (BB) on agent readiness against smolagents's 58.7 (C), and leads in 6 of 7 scored categories. Both do agent frameworks.\n\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- smolagents: grade C, 58.7/100, rank #739 of 1510. Markdown https://www.anchorterminal.com/tools/smolagents.md · JSON https://www.anchorterminal.com/api/v1/tools/smolagents.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### LlamaIndex Framework (BB)\n\nGood for: Python teams building retrieval-heavy agents over their own data, with many connectors.\n\nAhead on:\n- Reliability, 70 against 64\n- Agent ergonomics, 73 against 68\n- Security \u0026 auth, 74 against 66\n- Maintenance \u0026 community, 69 against 34\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### smolagents (C)\n\nGood for: Small Python projects and research that want code-writing agents with minimal abstraction.\n\nWatch for: No release since 1.26.0 on 29 May 2026, and few commits to main since August\n\n\n## Why the edge\n\n### Maintenance \u0026 community: LlamaIndex Framework +35\n\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- smolagents (34): v1.26.0 on 29 May 2026, 161 days before this check (10). No release in the 90 days to 6 November (0). 416 open issues and 1,045 open issues and pull requests on 6 November, with 144 issues opened in the 90 days to 3 November. Of the 50 newest, 26 had a comment and 1 was closed. Two 2026 CVE records say the vendor didn't respond to the reporter, and seven commits reached main from 8 August to 6 November (6). Python only, and the package is the current one (10). CI with actions pinned to commit SHAs and Dependabot for actions (8). 10+0+6+10+8 = 34.\n\n### Security \u0026 auth: LlamaIndex Framework +8\n\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- smolagents (66): Framework reading (telemetry defaults, approvals, guardrails, sandboxing). No telemetry found in the source (25). No human approval hook beyond step callbacks; the local executor restricts imports but the guide says it isn't a security tool, and isolation needs a remote executor (10). The secure execution guide covers LLM-generated code risks, without prompt-injection guidance for tool output (7). OpenTelemetry tracing through OpenInference and run inspection (12). SECURITY.md with private reporting and CVE credit, and the remote-executor RCE was fixed in public, but two 2026 CVE records say the vendor didn't respond (12). 25+10+7+12+12 = 66.\n\n### Reliability: LlamaIndex Framework +6\n\n- LlamaIndex Framework (70): Local-package reading. Official PyPI packages with Python 3.10 to below 4.0 (20). Public unit-test, type-check, lint, coverage and CodeQL workflows, with the type-check, lint and CodeQL runs on main passing on 3 November (25). 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). A dated, generated changelog per package, but core is 0.x and minors such as 0.13 and 0.14 carried breaking changes (8). Core isn't 1.0; Workflows is at 2.x, so partial (5). 20+25+12+8+5 = 70.\n- smolagents (64): Local-package reading. Official PyPI package with Python 3.10 or newer (20). A public tests workflow runs pytest on Python 3.10 and 3.12 for pushes and pull requests; whether main passes wasn't read (15). 416 open issues and 1,045 open issues and pull requests on 6 November, with 144 issues opened in the 90 days to 3 November. Of the 50 newest, 26 had a comment and 1 was closed. Two 2026 CVE records say the vendor didn't respond to the reporter, and seven commits reached main from 8 August to 6 November (6). Release notes on GitHub tags but no changelog file, and the remote WasmExecutor was removed in a minor release (8). 1.0 since 31 December 2024 (15). 20+15+6+8+15 = 64.\n\n### Agent ergonomics: LlamaIndex Framework +5\n\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- smolagents (68): Framework reading. MCPClient loads an MCP server's tools in a few lines (20). max_steps, planning intervals and final_answer_checks bound a run (16). Errors from tools and code go back to the model as observations (14). No built-in retry, idempotency or resume beyond replaying memory (8). Few required parameters and many providers, Python only, and the default model needs a Hugging Face token (10). 20+16+14+8+10 = 68.\n\n## Score by category\n\n| Category | Weight | LlamaIndex Framework | smolagents | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 70 | 64 | LlamaIndex Framework +6 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 85 | 81 | LlamaIndex Framework +4 |\n| Agent ergonomics | 13% (16.2 this run) | 73 | 68 | LlamaIndex Framework +5 |\n| Security \u0026 auth | 14% (17.5 this run) | 74 | 66 | LlamaIndex Framework +8 |\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) | 69 | 34 | LlamaIndex Framework +35 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 67 | 65 | LlamaIndex Framework +2 |\n| Negative events | ≤15 | -2 | -6 | |\n| **Total** | | **70 · BB** | **58.7 · C** | |\n\n## Facts side by side\n\n| Fact | LlamaIndex Framework | smolagents |\n| --- | --- | --- |\n| Kind | Agent framework | Agent framework |\n| Vendor | LlamaIndex | Hugging Face |\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 | Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-09-21 | 2026-05-29 |\n| Terms last updated | no document linked | 2022-09-15 |\n| Privacy policy last updated | 2026-08-24 | 2023-03-28 |\n| Customer content may train models | not read yet | not found in the text |\n| Terms restrict automated access | not read yet | not found in the text |\n| Terms restrict benchmarking | not read yet | not found in the text |\n| Terms or service can change without notice | not read yet | yes |\n| Arbitration or class-action waiver | not read yet | not found in the text |\n| Popularity | 53k stars, 1.3M PyPI/wk | 30k stars, 171k PyPI/wk |\n\n## Verdicts\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**smolagents.** A compact Python library for code-writing and tool-calling agents, with MCP tools, any model provider and remote sandboxes through E2B, Docker, Modal or Blaxel. The newest release is 1.26.0 of 29 May 2026, a critical remote-executor RCE took about eight weeks to fix, and the local executor isn't a security boundary.\n\n## Before you call either\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### smolagents\n\n1. Run CodeAgent with `executor_type` set to e2b, docker, modal or blaxel whenever the model or its inputs aren't trusted\n2. Use smolagents 1.24.0 or later to get the remote-executor deserialisation fix\n3. Set max_steps and final_answer_checks so a run stops on its own\n4. Pass structured_output explicitly to MCPClient to avoid the default-change warning\n5. Pin the version, since minor releases have removed APIs\n\n## Questions\n\n### Which is better for AI agents, LlamaIndex Framework or smolagents?\n\nLlamaIndex Framework scores 70 (BB) on agent readiness against smolagents's 58.7 (C), and leads in 6 of 7 scored categories.\n\n### Are LlamaIndex Framework and smolagents open source?\n\nYes. LlamaIndex Framework is open source (MIT). smolagents is open source (Apache-2.0).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/llamaindex-vs-smolagents.json, and with the fewest tokens: https://www.anchorterminal.com/compare/llamaindex-vs-smolagents.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"llamaindex\", \"b\": \"smolagents\"}`. From a terminal: `anchor compare llamaindex smolagents`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/llamaindex.json and https://www.anchorterminal.com/api/v1/tools/smolagents.json\n\n## Other comparisons with LlamaIndex Framework or smolagents\n\n- [AgentOS vs LlamaIndex Framework](https://www.anchorterminal.com/compare/agentos-vs-llamaindex.md)\n- [AgentOS vs smolagents](https://www.anchorterminal.com/compare/agentos-vs-smolagents.md)\n- [Agno vs LlamaIndex Framework](https://www.anchorterminal.com/compare/agno-vs-llamaindex.md)\n- [Agno vs smolagents](https://www.anchorterminal.com/compare/agno-vs-smolagents.md)\n- [BoxLang AI vs LlamaIndex Framework](https://www.anchorterminal.com/compare/boxlang-ai-vs-llamaindex.md)\n- [BoxLang AI vs smolagents](https://www.anchorterminal.com/compare/boxlang-ai-vs-smolagents.md)\n- [Claude Agent SDK vs LlamaIndex Framework](https://www.anchorterminal.com/compare/claude-agent-sdk-vs-llamaindex.md)\n- [Claude Agent SDK vs smolagents](https://www.anchorterminal.com/compare/claude-agent-sdk-vs-smolagents.md)\n- [CrewAI vs LlamaIndex Framework](https://www.anchorterminal.com/compare/crewai-vs-llamaindex.md)\n- [CrewAI vs smolagents](https://www.anchorterminal.com/compare/crewai-vs-smolagents.md)\n- [Cursor Agent SDK vs LlamaIndex Framework](https://www.anchorterminal.com/compare/cursor-agent-sdk-vs-llamaindex.md)\n- [Cursor Agent SDK vs smolagents](https://www.anchorterminal.com/compare/cursor-agent-sdk-vs-smolagents.md)\n- [Docker Agent vs LlamaIndex Framework](https://www.anchorterminal.com/compare/docker-agent-vs-llamaindex.md)\n- [Docker Agent vs smolagents](https://www.anchorterminal.com/compare/docker-agent-vs-smolagents.md)\n- [Agent Development Kit (ADK) vs LlamaIndex Framework](https://www.anchorterminal.com/compare/google-adk-vs-llamaindex.md)\n- [Agent Development Kit (ADK) vs smolagents](https://www.anchorterminal.com/compare/google-adk-vs-smolagents.md)\n- [guilds.run vs LlamaIndex Framework](https://www.anchorterminal.com/compare/guilds-run-vs-llamaindex.md)\n- [guilds.run vs smolagents](https://www.anchorterminal.com/compare/guilds-run-vs-smolagents.md)\n- [LangGraph vs LlamaIndex Framework](https://www.anchorterminal.com/compare/langgraph-vs-llamaindex.md)\n- [LangGraph vs smolagents](https://www.anchorterminal.com/compare/langgraph-vs-smolagents.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 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- [Mastra vs smolagents](https://www.anchorterminal.com/compare/mastra-vs-smolagents.md)\n- [Microsoft Agent Framework vs smolagents](https://www.anchorterminal.com/compare/microsoft-agent-framework-vs-smolagents.md)\n- [OpenAI Agents SDK vs smolagents](https://www.anchorterminal.com/compare/openai-agents-sdk-vs-smolagents.md)\n- [Pydantic AI vs smolagents](https://www.anchorterminal.com/compare/pydantic-ai-vs-smolagents.md)\n- [smolagents vs Strands Agents](https://www.anchorterminal.com/compare/smolagents-vs-strands-agents.md)\n- [smolagents vs TradingAgents](https://www.anchorterminal.com/compare/smolagents-vs-tradingagents.md)\n- [smolagents vs AI SDK](https://www.anchorterminal.com/compare/smolagents-vs-vercel-ai-sdk.md)\n",
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