"A tool or assistant to explore and debug my codebase" matching MCP servers:

Enables AI agents to query a beads store for issues, notes, comments, and memories, returning full verbatim content and relationship neighborhoods under an output budget.

Enables read-only searching, reading, and status inspection of a local Git-backed Markdown wiki via a minimal MCP toolset, without any network or write operations.

A demonstration MCP server that exposes basic arithmetic tools (add, subtract, ping) through FastAPI and shows how to integrate them with OpenAI's tool-calling API for LLM orchestration.

Enables token-efficient structural code exploration using tree-sitter AST parsing, with tools for symbol search, outlines, source unfolding, call graphs, and related-file discovery.

An MCP server for dataset exploration and analysis, enabling LLM clients to perform summary, correlation, distribution, missing value analysis, data cleaning, and statistical tests directly on CSV files.

An open-source AI-powered development assistant that connects Claude Desktop to your codebase via MCP, enabling semantic code search, AI-assisted editing, and persistent memory without additional subscriptions.

MCP server for creating and managing looks and dashboards in campaign-explore on bigbrain.me.

An MCP server that acts as an AI mentor for any codebase using dual-layer indexing, enabling codebase initialization, tutorial generation, and semantic search.

Evidence-backed, read-only codebase diagnostics for coding agents: secrets, dependency, RLS, and source-impact audits with a verify loop and PR review verdicts. Never writes files or uses the network by default.

Provides AI assistants with real-time visibility into your codebase's internal libraries, team patterns, naming conventions, and usage frequencies to generate code that matches your team's actual practices.

Zero-config MCP server that connects local codebases to AI assistants, providing secure project tree, regex search, file reading, and tech stack tools locally.

Enables AI assistants to perform interactive Python debugging with breakpoints, step execution, and variable inspection using the Debug Adapter Protocol (DAP) through an MCP server interface.

Enables any MCP client to debug programs through the Debug Adapter Protocol, supporting launch/attach, breakpoints, stepping, variable inspection, evaluation, and memory operations via a single debug tool.

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

A smart debugging agent that remembers errors, automatically diagnoses issues, and accumulates solutions for faster resolution.

Provides a code graph querying and visualization MCP server, enabling users to search, trace, and describe code components, overlay diffs, and explore architecture through natural language.

Provides comprehensive codebase analysis including project structure evaluation, cross-language duplicate detection, microservices validation, and configuration optimization with AI-powered pattern learning that generates actionable improvement reports.

Enables MCP clients such as Claude Desktop and Claude Code to query an indexed source repository through path-guarded tools for hybrid keyword-and-vector code search, file snippets, symbol explanations, reference lookups, and test-skeleton suggestions. Serves those results over stdio with cited file:line locations so agents can answer questions about a codebase and drive grounded code review.

MCP server for local codebase memory: semantic indexing, hybrid search, and clean code analysis (static + LLM) with retrievable project notes, designed to run fully local on modest hardware.

Enables an AI assistant to inspect, validate and step-debug Cardano transactions and Plutus scripts, including finding failing redeemers, explaining ledger/CBOR/CDDL errors, decompiling UPLC, and opening highlighted problems in cquisitor or de-uplc-web.