"A tool or feature in GitLab for parsing code" matching MCP servers:

The Token-Curated GitLab MCP Server: 80%+ Context Window Savings. Every time your agent fetches a pipeline with other servers, it wastes 1,600 tokens of avatar URLs, internal links, and HTML fluff. With @sumirati/mcp-gitlab, that drops from 1,840 to 190 tokens.

First gitlab mcp for you, building together

Enables agents to synthesize typed MCP tool schemas at runtime, validate Python ASTs for unsafe imports, compile sandboxed callable handlers, and hot-plug them into an active MCP runtime. It provides a zero-dependency, standard-library-only MCP server for safe just-in-time tool creation and execution.

Model Context Protocol (MCP) server for GitLab — exposes 1006 GitLab REST & GraphQL API operations as MCP tools (42 meta-tools / 57 enterprise), 24 resources, 38 prompts, and 17 completion types for AI assistants. Written in Go, single static binary, stdio and HTTP transport.

MCP router that fronts your other MCP servers behind a few small generic tools, so their tool definitions stay out of the context window and are discovered on demand.

MCP server for GitLab that provides 85 tools covering issues, merge requests, repositories, CI/CD, wiki, packages, and attachments, with support for both gitlab.com and self-hosted instances. It can read attachments so models can see screenshots and other files.

Enables AI agents and MCP clients to manage projects, merge requests, issues, pipelines, wiki, releases, tags, milestones, and more through stdio, SSE, or Streamable HTTP with PAT/OAuth authentication.

Enables AI agents to build and structurally validate Indian GST e-invoice JSON payloads (INV/CRN/DBN) and render IRP-returned signed QR strings as PNG images.

A Model Context Protocol server that enables AI assistants to interact with GitLab repositories, allowing tasks like managing merge requests, searching projects, and creating comments through RESTful API integration.

Audits MCP tool descriptions for quality and reliability, scoring them 0-100, detecting smells, and providing rewritten versions for better agent accuracy.

Gemini-powered MCP server for automated code review, analysis, and documentation.

Graph-based tool retrieval for LLM agents. Builds a tool graph from OpenAPI/MCP specs and retrieves multi-step workflows via hybrid search (BM25 + graph traversal + embedding), recovering accuracy from 12% to 82% with 79% fewer tokens. Also works as an MCP Proxy to aggregate multiple servers behind 3 meta-tools.

Checks a code repository without running it: Safe, Works and Complete scores with an A-F grade, catching leaked keys, dangerous calls, invented or lookalike packages, broken imports and missing project files. Standard-library Python; MCP tools scan, orphans and explain.

Give any LLM agent a real Android or iPhone. 62 MCP tools: tap, swipe, type, screenshot, screen-tree reading, app launch, camera, TTS, crash reports, batched execution. Android via ADB, iPhone via WebDriverAgent, on-device inference, Docker+KVM emulators. Works with Claude Code, Cursor, LangChain, LlamaIndex, and any MCP client. MIT.

Protects AI agents from bad tool outputs, schema mismatches, and tool poisoning by validating, sanitizing, and scoring reliability of tool responses.

MCP server that detects and guards against tool poisoning and prompt injection attacks in tool descriptions and schemas. It provides risk scoring, pattern detection, safe rewriting, and audit reports with zero external API cost.

Cross-chain cryptocurrency swaps via Chainflip. Get quotes, execute swaps, and track progress. No API key required to get started.

Lets a human review what an AI agent is about to post to a chat tool (Slack first) before it is sent. Renders the draft, destination and warnings (@here/@channel, unresolved mentions, format issues) in a neutral local HTML preview; never sends anything.

DREAM LAUNCHERS INTERIORS PRIVATE LIMITED

Validates AI-generated Python: syntax, lint, security scan and deterministic repair.