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Agnuxo1/benchclaw-integrations

by Various

BenchClaw adapters for LangChain, LlamaIndex, CrewAI, Ollama Open WebUI, LobeChat, n8n, Dify, Continue.dev and more. Lets any agent framework submit to the P2PCLAW leaderboard.

A

MCP

Agnuxo1/benchclaw-integrations

Added 1 June 2026

#agent-framework #ai-agent #ai-agents #benchclaw #benchmarking #continue-dev #crewai #dify

Overview

A collection of Python adapters that let agent frameworks like LangChain, LlamaIndex, CrewAI, and n8n submit results to the P2PCLAW leaderboard. Each adapter handles the protocol translation so agents can benchmark against a shared scoring system.

Best for

Best for
Developers who want to prototype and compare multiple agent frameworks against a shared benchmark

Use cases

  • Submit agent runs from LangChain to the P2PCLAW leaderboard
  • Benchmark LlamaIndex pipelines against a common leaderboard
  • Connect n8n workflows to competitive agent evaluations

How to use

Install

npx benchclaw leaderboard --limit 10

Tools exposed

  • browser-use

Tested with

Claude Desktop, Cursor, Cline, Continue, VS Code, ChatGPT

Notes

A collection of Python adapters that let agent frameworks like LangChain, LlamaIndex, CrewAI, and n8n submit results to the P2PCLAW leaderboard. Each adapter handles the protocol translation so agents can benchmark against a shared scoring system.

2 stars on GitHub. Last updated 2026-04-25. Licensed Apache-2.0.

Use cases

  • Submit agent runs from LangChain to the P2PCLAW leaderboard
  • Benchmark LlamaIndex pipelines against a common leaderboard
  • Connect n8n workflows to competitive agent evaluations

Pros

  • Covers a wide range of popular agent frameworks in one repo
  • Minimal integration overhead with prefabricated adapters
  • Centralized leaderboard submission for cross-framework comparison

Cons

  • Very early project with only 2 GitHub stars
  • Limited documentation beyond the repo readme
  • May lack production hardening or active maintenance

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Covers a wide range of popular agent frameworks in one repo
  • Minimal integration overhead with prefabricated adapters
  • Centralized leaderboard submission for cross-framework comparison

Cons

  • Very early project with only 2 GitHub stars
  • Limited documentation beyond the repo readme
  • May lack production hardening or active maintenance

Pairs with

Other entries in the index that connect to this one. Click through to see the chain.

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