"Resources and Information about Travel" matching MCP servers:

Free deterministic security scan of a public git repository (GitHub, GitLab, Codeberg, Bitbucket): vulnerable dependencies via OSV.dev, secret patterns, and config lint, returned as structured JSON. Tools: scan_repository(url), audit_pricing(). Runs locally over stdio (python3 web/mcp_stdio.py or the Dockerfile) and is also hosted at https://project-feldspar.com/mcp. MIT licence, stdlib-only. Buil

Gitbub mcp

Enables AI agents to analyze and diff binaries by driving Ghidra headless or inside its GUI, exposing native reverse-engineering tools such as listing functions and segments, searching strings, decompiling, disassembling, and following cross-references. Ships with a devcontainer and supports local stdio or remote HTTP deployment.

Enables MCP clients to load eight on-demand coding skills and inspect project repositories through bounded, read-only map, search, read, diff, checks, and style tools. It keeps context lean by loading skill bodies only when needed and limiting repository scan and output sizes.

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.

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

A read-only MCP server that lets a Claude chat explore your local repository and answer questions about it, returning synthesized answers with file:line references.

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 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.

Enables coding agents to index AscendC operators into a committed .uo graph and answer structural queries about Host, TilingKey, TilingData, and Kernel components via MCP.

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.

locidx

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

Local-first, code-aware engineering cognition for AI coding agents - persistent memory, contextual retrieval, and continuous cognition about your codebase.

An MCP server that scans codebases to extract structural information (classes, functions, etc.) with flexible filtering options and outputs in LLM-friendly formats.

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.