"Information about AWS MCP" matching MCP servers:

Enables querying any GitHub, GitLab, or Bitbucket repository and getting AI-generated answers about the codebase, powered by Gemini.

Enables asking natural-language questions about any GitHub repository and receiving answers grounded in the actual code, with read-only enforcement and automatic repository fetching.

Scans code strings for hardcoded secrets (AWS keys, tokens, private keys, etc.) and returns redacted findings, helping AI coding agents catch secrets before writing or committing code.

Scans diffs, files, and snippets for leaked secrets like AWS keys, GitHub tokens, and private keys, returning redacted findings while running fully locally without network calls.

truth is a deterministic fact-checker for the claims an AI coding agent makes about its own work.

Semantic git queries via MCP. Beyond git log — answer who/what/why about any line, file, or branch with blame, co-change, PR linkage.

MCP server for detecting publisher telemetry pipeline leaks in binary artifacts by scanning for sensitive strings like Sentry DSNs, Slack tokens, and AWS keys.

MCP server that provides npm package information for AI agents during TypeScript development.

Extracts deterministic architecture maps from codebases for AI agents, enabling queries about blast radius, routes, security findings, and production readiness without sending code anywhere.

Enables AI agents to search and retrieve details about Odoo code elements (models, fields, views, etc.) with exact file locations using MCP tools.

Provides coding agents with a compact map of a TypeScript/TSX codebase, enabling direct answers about symbol locations, imports, dependencies, and references while reducing token usage.

A mcp server to allow LLMS gain context about shadcn ui component structure,usage and installation

Enables storing and querying structured information about software code entities (classes, functions, files) and their relationships (calls, imports) along with qualitative observations like design decisions and change rationale.

Exposes Lachesis's code navigation tools over MCP, letting LLM agents ask precise compiler-level questions about dataflow, taint, callers, and guards in source code.

An MCP server for gitingest. It allows MCP clients like Claude Desktop, Cursor, Cline etc to quickly extract information about Github repositories including repository summaries, project directory structure, file contents, etc

Provides guidance and tools for the AWS Cloud Development Kit, including infrastructure patterns, GenAI constructs, and security compliance via CDK Nag. It streamlines development by generating Bedrock Agent schemas and providing comprehensive documentation for Lambda layers and AWS Solutions Constructs.

Provides tools for mapping and analyzing GitHub repositories. It allows users to set a GitHub Personal Access Token and retrieve detailed information about a specified repository, including its structure and summary statistics.

A local, read-only MCP server that provides AI coding agents with structural evidence about a repository, including dependency analysis and impact assessment, while naming the boundary of every answer without any LLM calls.

Give your coding agent the dependency graph it is about to change: scan, diff, explain, audit.

Read-only MCP server that provides AI agents with context about Unity project relationships, including scenes, prefabs, scripts, GUIDs, and code impact analysis.