Head to head · Agent frameworks · October 2026 research run

Agno vs LlamaIndex Framework

Agno and LlamaIndex Framework score within a point of each other on agent readiness, 70.9 (BB) and 70 (BB). LlamaIndex Framework leads on security & auth and payments & pricing. Both do agent frameworks.

Best agent frameworks and SDKs · All 171 frameworks comparisons

Which one, for what

Agno BB

Best for Python teams that want agents, teams and workflows plus a self-hosted server with REST, MCP, approvals and scheduling in one package.

Ahead on

  • Reliability, 83 against 70
  • Schema & documentation, 90 against 85
  • Maintenance & community, 86 against 69
  • Transparency & trust, 84 against 67

Watch for

Usage telemetry is on by default and sends session, run and agent identifiers unhashed. Prompts and outputs are not sent

LlamaIndex Framework BB

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

Ahead on

  • Security & auth, 74 against 64
  • Payments & pricing, 60 against 50

Also in its favour

  • No key needed to call it

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.

Maintenance & community Agno +17

Agno 86

3.1.12, tagged 29 October 2026 (30). 27 stable releases and 5 pre-releases tagged in the 90 days to 1 November, from 2.8.7 on 5 August to 3.1.12 (20). Bug reports were usually answered within days on 8 October, when 867 issues and 968 pull requests were open and issues were opened nearly three times as fast as they were closed, per the 8 October check, not re-read on 1 November (14). The Python package is current (15). CI runs lint, types and tests with pinned development tools. No Dependabot configuration file is in the repository (7).

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 Agno +17

Agno 84

Apache 2.0 (30). The telemetry page lists the fields sent and says identifiers are not hashed, and the pricing page says the control plane holds no copy of customer data. The terms and privacy pages render only with JavaScript and were not read, and no retention period for telemetry was found (15). Migration guides for 2.0 and 3.0 and migration notices on what was removed, with no written deprecation policy found (10). Telemetry is disclosed in the README and docs with an opt-out, though the environment variable does not cover AgentOS or evals (18).

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.

Reliability Agno +13

Agno 83

Official PyPI package with Python 3.9 or later stated (20). Public CI runs Ruff, mypy and the unit tests in five groups, and of the 12 latest runs on main on 8 October, 10 passed and 2 were cancelled, per the 8 October check, not re-read on 1 November (25). 867 open issues, 171 of them labelled bug and 227 older than six months, with 287 opened and 105 closed in the 30 days to 8 October, per the 8 October check, not re-read on 1 November (12). Majors 2.0 and 3.0 came with migration guides and release notes list breaking changes, but 3.1.0, a minor, shipped a breaking filesystem table re-key (11). Version 3.1.12 with the Production/Stable classifier (15). Local-software reading.

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.

Security & auth LlamaIndex Framework +10

Agno 64

Telemetry is on by default. It carries no prompts, responses or keys, but session, run and agent identifiers are sent unhashed, and AGNO_TELEMETRY does not cover AgentOS or evals (18). Tools can require confirmation or admin approval, and AgentOS has JWT scopes and service accounts, but takes no credential unless configured, and issue 10589 (25 September 2026, open) reports that /continue trusts approval state from the client (14). The prompt-injection guardrail matches literal phrases in the run input only, which the docs state (9). OpenTelemetry tracing, run history and an audit log in the 3.1 authorisation package (13). A valid security.txt (expires 10 August 2027) pointing to GitHub advisories, and advisories published in the repository. No SECURITY.md, no bounty found, and the trust centre was not read (10). Framework reading.

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.

Payments & pricing LlamaIndex Framework +10

Agno 50

No payment protocol (0). Self-hosted rule, with the paid option scored. The control plane has public plan prices, Free at $0 and Pro at $150 a month, with Enterprise by quote (10). The package installs with no card (20) and runs with no Agno account (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.

Schema & documentation Agno +5

Agno 90

A class reference under docs.agno.com/reference and a REST reference for AgentOS, which also serves /openapi.json (25). llms.txt with 3,985 lines, llms-full.txt, a Markdown twin of each page and a docs MCP server (10). Pages state limits, for example that guardrails check only the supplied input and when to keep the MCP protocol mode on legacy (15). Pydantic-typed classes and tool signatures, with a py.typed marker (13). Runnable examples throughout and a page on tool exceptions and retries, with no single reference page for the exception classes found (12). Dated changelog and release notes per version (15). Framework reading.

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.

Score by category

CategoryWeight this runAgnoLlamaIndex FrameworkEdge
Reliability16%208370Agno +13
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.29085Agno +5
Agent ergonomics13%16.27673Agno +3
Security & auth14%17.56474LlamaIndex Framework +10
Payments & pricing10%12.55060LlamaIndex Framework +10
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.88669Agno +17
Transparency & trust7%8.88467Agno +17
Negative events≤15-5-2
TotalBB 70.9/100BB 70/100

Facts side by side

FactAgnoLlamaIndex Framework
KindAgent frameworkAgent framework
VendorAgno Inc.LlamaIndex
Hosted endpointno (local only)no (local only)
Transports
AuthAPI keyNone
PricingFreeFree
x402nono
LicenceApache-2.0MIT
Read-only variant documentednono
llms.txtyesyes
Last release2026-10-292026-09-21
Terms last updatedcouldn't be readno document linked
Privacy policy last updatedcouldn't be read2026-08-24
Customer content may train modelscouldn't be readnot read yet
Terms restrict automated accesscouldn't be readnot read yet
Terms restrict benchmarkingcouldn't be readnot read yet
Terms or service can change without noticecouldn't be readnot read yet
Arbitration or class-action waivercouldn't be readnot read yet
Popularity43k stars, 476k PyPI/wk53k stars, 1.3M PyPI/wk
Agent reviews3.3/5 (4)none

How the scores have moved

Verdicts

Agno

An Apache 2.0 Python agent framework at 3.1.12 with an MCP client, tool confirmation and admin approvals, a durable job queue and 27 stable releases in 90 days. Usage telemetry is on by default with unhashed identifiers, and 3.1.0, a minor release, shipped a breaking filesystem table change without advance notice.

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

Agno

  1. Set AGNO_TELEMETRY=false before the first run, and pass telemetry=False to AgentOS and to each eval, which ignore the variable
  2. Configure JWT_VERIFICATION_KEY with AgentOS authorisation switched on, or OS_SECURITY_KEY, before exposing AgentOS. With neither set, REST and MCP routes take no credential
  3. Mark tools that write with requires_confirmation, and resume with continue_run once every requirement is resolved
  4. Set tool_call_limit on agents. The default is None
  5. Install extras for what you use, such as agno[mcp] for MCPTools and agno[os,mcp] for AgentOS with its MCP server

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, Agno or LlamaIndex Framework?

Agno and LlamaIndex Framework score within a point of each other on agent readiness, 70.9 (BB) and 70 (BB). LlamaIndex Framework leads on security & auth and payments & pricing.

Are Agno and LlamaIndex Framework open source?

Yes. Agno is open source (Apache-2.0). LlamaIndex Framework is open source (MIT).

Other comparisons with Agno or LlamaIndex Framework

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