"Y Combinator" matching MCP servers:

MCP server for see-u-ui component library, allowing AI assistants to query component props/events/slots/examples on demand.

MCP server that exposes tools to route natural language queries to typed IDs, describe catalog entries, and list repository verification commands for the m-dev-tools organization.

Enables searching J-Quants API endpoints, retrieving detailed documentation, generating executable sample code, and answering FAQs via MCP clients like Claude Desktop.

MCP server for PDF manipulation — create PDFs from Markdown with tables and formatting, fill forms, merge, split, encrypt, add QR codes, and more. 16 tools, zero external binaries, TypeScript-native. Install with npx -y @aryanbv/pdf-toolkit-mcp.

MCP server that recommends which npm/PyPI libraries to use or avoid, with concise verdicts, alternatives, and code snippets, keeping responses under 500 tokens.

Provides LLMs with real-time access to up-to-date documentation from PyPI, npm, crates.io, GoDocs, DockerHub, GitHub, and GCP, preventing outdated code generation and API hallucinations.

Enables AI clients like Claude Desktop to search J-Quants API endpoints, get detailed information, reference implementation patterns, and access FAQ answers using MCP.

Enables querying documents through a Langflow backend using natural language questions, providing an interface to interact with Langflow document Q\&A flows.

Helps migrate projects from AI SDK 4.x to 5.0 by generating a migration checklist and searching the official migration guide for code and data changes.

A Python-based MCP server that enables document-based question answering by processing PDF, TXT, and Markdown files through OpenAI's API. It provides hallucination-free responses based strictly on document content using semantic search and includes a web interface for management.

MCP server for the hy-app component library, enabling AI editors to search components, retrieve APIs and examples, check platform support, access hooks and tools, and validate component usage.

Enables document-based question answering using OpenAI's GPT-4 with semantic search and embeddings. Upload PDF, TXT, or Markdown files and get answers strictly based on document content with source attribution and confidence scores.

An OpenAPI-driven MCP agent hub that dynamically generates MCP tools from Swagger/OpenAPI specs, enabling conversational interaction with backend APIs through natural language.

Enables AI agents to look up official EYD Edisi Kelima spelling rules and check or correct Indonesian text for common errors such as nonstandard prepositions, particles, affixed forms, and punctuation through tool calls.

A high-performance Model Context Protocol server that enables AI agents to extract text, images, and metadata from PDF documents using parallel processing. It features intelligent Y-coordinate content ordering to preserve natural reading flow and supports both local files and URL-based sources.

Automates generation of Work Breakdown Structure (WBS) diagrams and project documents. Supports Mermaid, PNG, and .docx export for project MINTRANET.

Enables AI assistants to interact with OpenAPI documents for analysis, validation, and management through structured interfaces.

An MCP server that provides version-pinned, deterministic documentation sourced from DevDocs.io to AI assistants (Claude, RooCode, Cline, Copilot etc.) and also via offline mode. Not via Scraping! But using the supported downloading option from devdocs.

Enables AI clients to browse, read, update, and search a document store through tools, resources, and prompts, including summarizing and comparing documents via URI-addressable resources and reusable prompt templates.

Enables validation and retrieval of metadata from Markdown files in the Subordinación y Valor project. Validates metadata against project specifications and extracts structured metadata from Markdown documents.