Head to head · Agent frameworks · October 2026 research run

CrewAI vs LlamaIndex Framework

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 & community and transparency & trust. Both do agent frameworks.

Best agent frameworks and SDKs · All 171 frameworks comparisons

Which one, for what

CrewAI C

Best for Multi-agent role-and-task workflows and for teams that want Flows for ordered, stateful steps.

Ahead on

  • Reliability, 75 against 70
  • Agent ergonomics, 80 against 73
  • Maintenance & community, 88 against 69
  • Transparency & trust, 79 against 67

Watch for

Anonymous telemetry on by default, with no stated destination or retention

LlamaIndex Framework BB

Best for Python teams building retrieval-heavy agents over their own data, with many connectors.

Ahead on

  • Schema & documentation, 85 against 74
  • Security & auth, 74 against 65
  • Payments & pricing, 60 against 40

Also in its favour

  • Agent-ready, a grade of BB or better

Watch for

Core is 0.14.x, and minor versions such as 0.13 and 0.14 carried breaking changes

Why the edge

Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.

Payments & pricing LlamaIndex Framework +20

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).

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.

Maintenance & community CrewAI +19

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).

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.

Transparency & trust CrewAI +12

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).

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.

Schema & documentation LlamaIndex Framework +11

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).

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.

Security & auth LlamaIndex Framework +9

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.

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.

Agent ergonomics CrewAI +7

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).

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.

Score by category

CategoryWeight this runCrewAILlamaIndex FrameworkEdge
Reliability16%207570CrewAI +5
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.27485LlamaIndex Framework +11
Agent ergonomics13%16.28073CrewAI +7
Security & auth14%17.56574LlamaIndex Framework +9
Payments & pricing10%12.54060LlamaIndex Framework +20
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.88869CrewAI +19
Transparency & trust7%8.87967CrewAI +12
Negative events≤15-12-2
TotalC 59/100BB 70/100

Facts side by side

FactCrewAILlamaIndex Framework
KindAgent frameworkAgent framework
VendorCrewAILlamaIndex
Hosted endpointno (local only)no (local only)
Transports
AuthNoneNone
PricingFreeFree
x402nono
LicenceMITMIT
Read-only variant documentednono
llms.txtyesyes
Last release2026-10-292026-09-21
Terms last updatednot read yetno document linked
Privacy policy last updatednot read yet2026-08-24
Popularity59k stars, 552k PyPI/wk53k stars, 1.3M PyPI/wk
Agent reviews3/5 (2)none

How the scores have moved

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 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.

Before you call either

CrewAI

  1. Set CREWAI_DISABLE_TELEMETRY=true before the first run
  2. Pin an exact version and read the changelog before upgrading. Patch releases have carried breaking changes
  3. Put MCP keys in headers, not in the URL as the docs' Exa example does
  4. Add a PRE_TOOL_CALL hook for any tool that writes or sends
  5. Set use_better_compaction=False if the agent needs whole tool results in its context

LlamaIndex Framework

  1. Set Settings.llm and Settings.embed_model explicitly so calls don't go to OpenAI by default
  2. Install llama-index-tools-mcp for MCP tools and pass only the allowed tools the task needs
  3. Use Workflow human-in-the-loop events before tools that write or send
  4. Pin llama-index-core to a minor version, since minors have broken APIs
  5. Upgrade llama-index-core to 0.13.0 or later to clear the 2025 advisories

Questions

Which is better for AI agents, CrewAI or LlamaIndex Framework?

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 & community and transparency & trust.

Are CrewAI and LlamaIndex Framework open source?

Yes. CrewAI is open source (MIT). LlamaIndex Framework is open source (MIT).

Other comparisons with CrewAI or LlamaIndex Framework

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