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MCP servers and skills: search, filter by where they run, and compare.
MCP servers and skills: search, filter by where they run, and compare.
Turbocharge Claude Code, Cursor, Codex, Gemini & every coding agent: faster, cheaper, with contextual understanding specific to your codebase.
Node.jsMIT★ 11kNo key
Benchmark your MCP server.
Node.jsMIT★ 11No key
Local-first MCP server that tells coding agents which files to read, and how sure it is. 97% Hit@10 on Java (SWE-bench Multilingual), 89% on Python (SWE-bench Lite), zero LLM cost. mcp-brain calibrate
PythonMIT★ 5No key
基于 claude-code-from-scratch 二次开发的 coding agent(TS):加入自我纠错闭环、本地 embedding 记忆、MCP、SWE-bench 评测 | A coding agent (TS) built on claude-code-from-scratch, adding self-correction, local embedding memory, MC
Node.jsMIT★ 1Few starsNo key
A blazing-fast, memory-safe neural network library for Rust that brings the power of FANN to the modern world.
Node.jsMIT★ 387No key
Zero-LLM structural code retrieval for AI coding agents — tree-sitter index, BM25+dense+structural fusion, served over MCP.
PythonMIT★ 7No key
A hermetic, no-root sandbox that emits a signed, independently-verifiable receipt that the isolation seal held — verifiable governance for AI agents (Rust).
SkillMIT★ 3Few starsNo key
Architectural Moat: JIT-JEV Context OS — Epistemic runtime & JEV System 1 context gate for AI agents (L0 SQLite WAL <3ms, Epistemic Invariants I1–I10, CERN Zenodo DOI: 10.5281/zenodo.22649542)
PythonMIT★ 8No key
Node.jsMIT★ 2Few starsNo key
Context engine for coding agents. Indexes a repo into a multi-layer knowledge graph and serves precise architectural context over MCP. 78.2% on SWE-bench Verified at $0.22/instance. MIT.
PythonMIT★ 2Few starsNo key
Graft - open-source context layer for large codebases (built from trailhq/Graft, v0.19.0)
Node.jsMIT★ 2Few starsNo key
Your coding agent is smart. Your legacy codebase is the problem. Reify gives it the context to understand and safely change large, unfamiliar codebases — 100% locally.
SkillApache-2.0★ 3Few starsNo key
decision-engine, autonomous-agents, modernbert, pytorch, model-context-protocol, system-1, developer-tools, pr-gating
SkillApache-2.0★ 2Few starsNo key
Next-Generation Distributed Multi-Agent Runtime & Swarm Substrate uniting Super-Memory, Cyclical Swarms, 24/7 Durable Daemons, Multimodal Streaming, VLA Safety Governors, and Benchmark Evaluators.
PythonApache-2.0Few starsNo key
Transparent feedback compression middleware for LLM coding agents
PythonMIT★ 1Few starsNo key
Find the agent-memory benchmark that fits your system in one offline command.
SkillMITFew starsNo key
Make every coding agent faster, cheaper, and more accurate with a persistent local code graph that learns from each session.
GoApache-2.0★ 2Few starsNo key
An open-source, cost-efficient (<zsh.50/task), and extensible Agentic Software Development Life Cycle (AIDLC) framework
SkillApache-2.0Few starsNo key
⚡ Universal High-Performance Speculative Tool Execution Proxy for the Model Context Protocol (MCP). Reduces P95 latency by 35%-48%.
PythonMIT★ 1Few starsNo key
Xanther Context Engine MCP Server — Give your coding agent deep codebase understanding
SkillMIT★ 2Few starsNo key
Multi-agent reasoning MCP server for Claude Code. Spawns parallel research agents to find knowledge LLMs don't have. +23.1% on Terminal Bench 2.0 SWE tasks.
SkillMIT★ 1Few starsNo key
Task-adaptive repository context engine for coding agents: local MCP, exact token budgets, and dependency-aware retrieval.
Node.jsMIT★ 1Few starsNo key
Reproducible RL environments for evaluating coding agents on real software-engineering tasks through MCP tools. Deterministic verification, golden reference solutions, and CI that validates the enviro
PythonMITFew starsNo key
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