"MCP server for contextual codebase analysis and task-focused code understanding" matching MCP servers:

Persistent memory for AI coding agents: local-first semantic search, dependency graphs, git history.

A Model Context Protocol server that provides Retrieval-Augmented Generation capabilities using Contextual AI, enabling AI interfaces like Cursor IDE and Claude Desktop to query domain-specific knowledge with context-aware responses and source citations.

Enables AI assistants to access options analysis data, market research tools, portfolio risk snapshots, and platform context via 32 tools.

Records and scores prospective equity earnings predictions made by AI agents, allowing comparison of different agent configurations.

A production-grade MCP server for the Code-Fundi API, enabling AI agents to map codebases, search semantically, and analyze blast radius. It provides tools for repository management, AI-powered research, and impact analysis before shipping changes.

Enables coding agents to run deterministic, zero-dependency AST static analysis over source code, building call graphs and dependency metrics to find orphaned functions, unreachable methods, breaking API surface diffs, and token-bloat clusters, then return a structured refactoring plan. It plugs into MCP clients like Claude Desktop, Cursor, and Windsurf via a single Python entrypoint.

Enables deterministic AST static analysis and call-graph auditing to identify orphaned functions, unreachable methods, and token-bloat clusters, producing refactoring plans that reduce context waste.

embedded code search engine CLI -AST based that just works - improves speed and efficiency for coding agent

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.

Enables async-first working practices by providing tools to draft decision docs, convert meetings to async artifacts, score status updates, and triage sync vs async tasks. It also offers reference tools for the Open and Async book's principles and coaching prompts.

A Model Context Protocol (MCP) server designed to easily dump your codebase context into Large Language Models (LLMs).

Persistent project memory + architectural decisions + pre-execution safety hooks for Claude Code. Local-only storage, multi-repo workspace, automatic knowledge extraction via background auditor.

This read-only MCP Server allows you to connect to Azure Analysis Services data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out the first managed MCP platform: CData Connect AI (https://www.cdata.com/ai/).

Allows agents to lookup code snippets in your project. Uses a remote MCP server with a collection of code snippets, with support for automatic project language detection.

Enterprise-grade code intelligence server for AI assistants that analyzes codebases for due diligence, tech debt, security vulnerabilities, and code quality.

Enables AI assistants to surgically extract and analyze code, reducing token usage and costs by up to 200x compared to reading entire files.

A local, cross-editor MCP server that provides persistent memory for coding agents, capturing and recalling decisions, conventions, and fixes across sessions without API keys.

Injects the Code-Me brand identity, tone, and visual guidelines into LLMs with zero latency using built-in context files.

Deterministic code review MCP server that provides tools for file selection, rule matching, comment positioning, and reflection, ensuring stable review quality without LLM calls.

This MCP wraps Bitrefill public API to allow agents to search for products and shop using cryptocurrencies like Bitcoin, Ethereum, Solana, and many more.