"Requesting an answer from a specific document" matching MCP servers:

A sophisticated server that enables AI assistants to automatically analyze codebases and generate comprehensive, professional documentation.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

Enables AI agents to generate and retrieve a contextual document for a git branch, summarizing repository state, changes, and freshness, so they can understand the branch without scanning the entire codebase.

Provides GDB and clangd-based tools for debugging C++ programs, enabling step execution, variable inspection, diagnostics, and combined runtime-static analysis.

A lean, local knowledge graph that joins a repo's code to its aSPARK delivery artifacts, enabling agents to trace user stories to code and assess impact of changes, served over MCP.

Zero-dependency MCP server inspector for protocol conformance, tool annotations, and capability checks.

PCI DSS v4.0.1 compliance scanner for Go payment services, delivered as an MCP server. Every finding maps to a specific PCI DSS requirement ID. Taint-aware cardholder data flow analysis with PCI SSC FAQ semantics, designed to complement broad SAST tools like Semgrep and CodeQL - not replace them.

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.

Enables Claude to explore, analyze, and answer questions about any public GitHub codebase by connecting to DeepWiki's AI-powered documentation.

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

Gives an AI agent complete knowledge of a specific DevExpress XAF application: its entities, controllers, actions, business rules, Model Editor customizations, custom property editors and the version-gated data migrations that ran once on a production database. Reads the source with Roslyn without compiling it, so it works on a branch that does not build and needs no DevExpress licence.

Enables natural-language Q&A over codebases via MCP, using AST-aware chunking, hybrid retrieval, reranking, and call-graph expansion to answer with file:line citations and impact analysis.

An MCP server that reverse-engineers a rebuild spec (CLAUDE.md, config, and mutation-tested tests) from an existing app, enabling coding agents to rebuild the app cleanly against that spec.

Cartograph is an MCP server that provides agent-native code intelligence by building a queryable code graph from a repository using tree-sitter and SQLite. It offers tools for symbol lookup, call graph traversal, blast radius analysis, and architecture overview to help coding agents answer structural questions about code.

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.

Mason indexes your codebase into a persistent concept map linking features and flows to their implementing files, so AI agents can answer "where is X implemented" without running grep/glob. It also provides pre-edit impact analysis and generates CLAUDE.md files from structured analysis of git history, architectural file sampling, and test mappings.

locidx

An installable MCP server that reviews diffs/PRs against a target repository's own coding conventions, learned via RAG over its code, docs, and lint config, citing specific file:line sources.

Serves graph-native code questions from a TypeScript codebase as an MCP server. It extracts structural graphs via tree-sitter and HydraDB to answer callers, impact, and context queries.

Score your specs before an LLM builds from them. Scores on 4 axes (completeness, clarity, constraints, specificity), calculates a balance score, and returns a verdict with radar chart visualization.