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26 repos for code-agents · Connectors · ResearchClear
0xK3vin/
MegaMemory

Persistent project knowledge graph for coding agents. MCP server with semantic search, in-process embeddings, and web explorer.

551
marckrenn/
rtfmbro-mcp

rtfmbro provides always-up-to-date, version-specific package documentation as context for coding agents. An alternative to context7

92
ref-tools/
ref-tools-mcp

Helping coding agents never make mistakes working with public or private libraries without wasting the context window.

1.2k
timescale/
tiger-cli

Tiger CLI is the command-line interface for Tiger Cloud. It includes an MCP server for helping coding agents write production-level Postgres code.

117
mathomhaus/
guild

Shared context, memory, and task coordination across AI coding agents. Single Go binary, local SQLite, hybrid keyword and semantic search.

305
AVIDS2/memorixConnectors

Open-source cross-agent memory layer for coding agents via MCP. Compatible with Claude Code, Codex, Cursor, Windsurf, Gemini CLI, Antigravity, OpenClaw, Hermes Agent, Oh-my-Pi, Pi, Copilot, Kiro, OpenCode, and Trae.

751
CodeAlive-AI/
codealive-mcp

Context engine for large codebases, exposed through MCP. Gives AI coding agents precise repository context; benchmarked at frontier-agent quality with ~25x lower model cost and 45% fewer tokens with semantic search.

90
trailhq/
Graft
trailhq/GraftConnectors

Turbocharge Claude Code, Cursor, Codex, Gemini & every coding agent: faster, cheaper, with contextual understanding specific to your codebase.

7k

Local code intelligence MCP server and CLI for AI coding agents

740
okf-memory/
okf-agent-memory

Git-native persistent memory for AI coding agents. Implements Google OKF v0.2 with sub-300µs in-memory BM25 search, embedded MCP server, and progressive disclosure. Slashes token bloat by 80% with zero external databases or dependencies. Built in pure Go.

547

The go-to web for your AI coding agent — local-first search, fetch, crawl & research over MCP. No API keys, no cloud, $0/query. Public beta.

5.2k

Nia is a context-augmentation layer for agents, primarily designed for coding agents. It provides them with an up-to-date knowledge base and improves their performance by 27%.

74
withqwerty/
football-docs

Searchable football data provider documentation for AI coding agents. Like Context7 for football data.

66
mnemox-ai/
idea-reality-mcp

Pre-build reality check for AI coding agents. Scans GitHub, HN, npm, PyPI, Product Hunt. MCP server. 290+ stars.

815

Code search MCP for Claude Code. Make entire codebase the context for any coding agent.

13k
morluto/reaConnectors

Reverse engineer anything with agents, from app behavior down to native binaries.

400
EtienneChollet/
ontomics

Extract domain knowledge from codebases to reduce LLM token consumption by 20x and time in agentic search by 10x — gathers and makes concepts, naming conventions, and vocabulary queryable via MCP.

41
krokozyab/
Agent-Fusion

Agent Fusion is a local RAG semantic search engine that gives AI agents instant access to your code, documentation (Markdown, Word, PDF). Query your codebase from code agents without hallucinations. Runs 100% locally, includes a lightweight embedding model, and optional multi-agent task orchestration. Deploy with a single JAR

73

Context7 Platform -- Up-to-date code documentation for LLMs and AI code editors

62k
1 add

Grounded Docs MCP Server: Open-Source Alternative to Context7, Nia, and Ref.Tools

1.7k
Ikalus1988/
MisakaNet

📚 A zero-dependency, git-backed micro-lesson library for AI Agents to asynchronously share and search verified debugging experience. Python stdlib only. | https://misakanet.org

488
Intina47/
context-sync

Local persistent memory store for LLM applications including continue.dev, cursor, claude desktop, github copilot, codex, antigravity, etc.

192
pinoox/
neuromesh

The Biomimetic Context Engine & Neural Runtime for AI Coding Assistants

85
morluto/flameoxConnectors

Runtime evidence that helps agents trace, profile, and burn down hotspots in application and native code, GPU kernels, and inference stacks.

121