"Information about guardrails" matching MCP servers:

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.

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

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

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

Enforces AST-based architectural guardrails on AI-generated code, blocking writes that violate maintainability, security, or complexity rules and prompting immediate refactoring.

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.

Enables AI agents to run Shipcheck on local JavaScript/TypeScript repositories, scanning for launch risks like exposed env vars, unsigned webhooks, and missing security guardrails.

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 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.

unerr is operational memory—a local runtime behind your agent's MCP enforcing shared code graphs, session memory & guardrails. No silent breakages. No context rot.

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.

An MCP server that ingests Spring Boot REST microservices from GitHub, builds a request-flow ontology, and enables natural-language queries about code with flow-aware answers and citations.

Remote MCP server that gives coding agents verified, version-pinned answers about fast-moving frameworks, starting with Expo SDK 54.

Helps AI read GitHub repository structure and important files. Want to quickly understand what a repo is about? Prompt it with "read https://github.com/adhikasp/mcp-git-ingest and determine how the code technically works".

Enables natural language queries about JavaScript/TypeScript codebases using graph and vector search. Allows finding functions by semantic description, callers, callees, and function details.

Enables AI coding tools to query your live codebase for routes, import graph, domain context, and blast radius, eliminating hallucinations about project structure.

Serves a facts-only index of SWAT+ Fortran source as read-only MCP tools, enabling coding assistants to answer exhaustive questions about loops, call graphs, file I/O, and other source facts with file and line references.