"Repository intelligence MCP server for code analysis and dependency graphs" matching MCP servers:

Serves a central playbook hub that provides situational guidance to LLM agents, lets clients list available playbooks, fetch procedural guidance, and apply graph mutations for persistent self-evolution.

Persistent memory for AI agents. Store, recall, and share knowledge across sessions with five MCP tools: remember, recall, context, forget, and share. Includes semantic search and agent/user/org scoping.

Integrates Google's Gemini AI models into Claude Code and other MCP clients to provide second opinions, code comparisons, and token counting. It supports streaming responses and multi-turn conversations directly within your existing AI development workflow.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

Enables AI agents to break down complex tasks into manageable pieces using a structured JSON format with task tracking, context preservation, and progress monitoring capabilities.

Transform your codebase into professional architectural decision records with intelligent AI analysis

Analyzes frontend project code (React, Vue, Angular) and converts it into AI-understandable flow diagrams and object structures. Provides tools for code analysis, variable/function/component inspection, and project structure insights.

Provides a hand-written MCP server integrated with a LangGraph agent to benchmark multiple agent topologies and measure their failure rates.

Enables AI agents to perform workspace file operations (read/write/recover) with transaction-safe guarantees, durable recovery, and explicit human approval via a separate Broker.

Provides image recognition capabilities to Codex/Claude Code by routing 'look at screen/screenshot' requests to a multimodal model via an API relay. Enables UI automation agents to analyze local screenshots and return descriptions or structured JSON coordinates.

Enables multi-agent council workflows for coding assistants, providing parallel independent reviews, plans, brainstorms, validation, and research with strict read-only boundaries.

This MCP server is designed for planning with Claude Code, Cline, or Cursor and making changes with Cerebras to maximize speed and intelligence while avoiding API limits. It uses the Qwen 3 Coder model for high-quality code generation and can be embedded in IDEs.

Executes Python code in isolated rootless containers while proxying MCP server tools, reducing context overhead by 95%+ and enabling complex multi-tool workflows through sandboxed code execution.

Provides access to a library of 18 specialized skills, project templates, and prompt patterns for Claude Code. It enables automated workflows for feature development, security audits, and system maintenance through multi-agent collaboration.

A security filter that blocks dangerous code patterns by comparing normalized structural syntax trees against a blacklist of known threats using vector embeddings. It acts as a gatekeeper to prevent malicious code execution by identifying dangerous structures regardless of specific identifiers or literals.

Domain-expert SMB sales playbooks for AI agents. Discovery questions, objection handlers, cold email + LinkedIn DM templates, BANT/MEDDIC frameworks, closing tactics. Built by an ex-Criteo (268% quota) / ex-Deel ($12B) / ex-HBO / ex-Bloomberg enterprise AE. Use when your AI SDR needs real human-tested sales artifacts.

Product entry point and evidence-discipline layer for strategic intelligence agents.

Enables orchestration of multiple Claude Code sessions for complex multi-task coding projects with HEAD/SUB coordination and dependency-based task execution.

Delegates expensive or long-running AI tasks to Kubernetes-hosted Claude agents running on OpenShift. Enables creating, managing, and monitoring remote agentic sessions for complex work like codebase analysis and security audits.

An implementation of Claude Code as a Model Context Protocol server that enables using Claude's software engineering capabilities (code generation, editing, reviewing, and file operations) through the standardized MCP interface.