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ashlesh-t/cognirepo

by Various

Local cognitive infrastructure for AI coding agents — semantic memory, repository intelligence, and MCP tools to reduce token usage.

A

MCP

ashlesh-t/cognirepo

Added 15 June 2026

#ai #ai-agents-automation #ai-agents-cli #ai-agents-mcp #mcp #mcp-servers

Overview

Local cognitive infrastructure for AI coding agents. It provides semantic memory, repository intelligence, and MCP tools to reduce token usage.

Best for

Best for
Developers building custom AI coding agents who need local repository awareness and token efficiency

Use cases

  • Enhancing AI coding agents with local semantic memory for repository context
  • Analyzing codebases to provide repository intelligence to AI tools
  • Reducing API token consumption in AI-driven development workflows

How to use

Install

pip install pipx --user

Tools exposed

  • DEFINED_IN
  • CO_OCCURS
  • RELATES_TO
  • QUERIED_WITH

Tested with

Claude Desktop, Claude Code, Cursor, VS Code, ChatGPT

Notes

Local cognitive infrastructure for AI coding agents. It provides semantic memory, repository intelligence, and MCP tools to reduce token usage.

9 stars on GitHub. Last updated 2026-06-14. Licensed MIT.

Use cases

  • Enhancing AI coding agents with local semantic memory for repository context
  • Analyzing codebases to provide repository intelligence to AI tools
  • Reducing API token consumption in AI-driven development workflows

Pros

  • Reduces token costs by caching and intelligently retrieving context
  • Runs locally, offering privacy and offline capabilities
  • Open-source Python tool with no vendor dependency

Cons

  • Low community adoption and limited stars suggest early-stage project
  • Requires local setup and configuration of MCP integration
  • Token savings depend on the specific coding agent and usage patterns

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

Pros

  • Reduces token costs by caching and intelligently retrieving context
  • Runs locally, offering privacy and offline capabilities
  • Open-source Python tool with no vendor dependency

Cons

  • Low community adoption and limited stars suggest early-stage project
  • Requires local setup and configuration of MCP integration
  • Token savings depend on the specific coding agent and usage patterns

Pairs with

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

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