"Informational MCP Servers with Croissant Dataset Format Support" matching MCP servers:

Validates MLCommons Croissant dataset metadata (JSON-LD) for schema compliance, as a stateless MCP server.

MCP server that gives Claude programmatic access to a local En Croissant chess opening trainer, enabling conversational opening prep by reading its SQLite database, PGN files, and Lichess API. It supports repertoire review, due cards, and opponent statistics directly from chat.

Enables version-controlled golden dataset management and semantic evaluation for RAG/LLM pipelines using TF-IDF cosine similarity, without requiring an LLM API key.

A tool that enables automated browser control using Pyppeteer within the MCP framework, allowing navigation, screenshot capture, and element interaction with websites.

An MCP server that searches HuggingFace/Kaggle for datasets, detects their domain, and generates a matching preprocessing script. It turns natural-language dataset queries into runnable, domain-aware preprocessing pipelines.

Enables querying JSON/JSONL social datasets in Claude Desktop via MCP tools, using DuckDB as the backend database.

Enables interaction with the Hugging Face Dataset Viewer API, allowing users to browse, search, filter, and analyze datasets hosted on the Hugging Face Hub.

Enables AI clients to explore and analyze CSV datasets via tools for dataset overview, statistical summaries, missing value analysis, duplicate detection, correlation analysis, and outlier detection.

Enables AI assistants to work with Chapel code, including compiling, linting, and accessing educational primers.

Unified MCP server for discovering open datasets across Hugging Face, Zenodo, and Kaggle, with ranked search results and one-click Colab starter code generation.

Enables collection, enhancement, and quality scoring of authentic Amharic datasets, with integration for AI models like Gemini and Qwen.

Enables AI harnesses to maintain a persistent memory layer backed by a local SQLite file, providing MCP tools to add, search, deprecate, and synchronize facts without deleting history.

A learning MCP server that demonstrates tools and resources using FastMCP, with a greet tool and UI capabilities.

Enables natural language querying and semantic search over a bilingual customer support ticket dataset using SQL and embeddings.

Manages the state of a chess game for LLMs/agents without suggesting moves, providing tools to create/reset game, add moves, get status, and check legality.

Provides seamless access to the Protein Data Bank in Europe (PDBe) API and search capabilities, enabling AI clients to query protein structures, perform advanced searches, and retrieve structural biology data.

A workspace of six MCP servers—grounded-cv (hybrid RAG with citations), repo-intel (GitHub repo intelligence), web-research (safe web search/extraction), ats-jobs (unified ATS job boards), outcome-ledger (durable task ledger), and coding-workflows (code review & planning)—purpose-built for agentic hiring evaluations.

Provides a framework for running multiple MCP servers using FastAPI, stdio, and streamable-http transports, with an echo tool for testing and integration with MCP Inspector.

An MCP server that acts as a governed customer-support tool, resolving questions only when the knowledge base supports a cited, grounded answer and honestly escalating everything else with provenance and evidence.

Exposes order status lookup and knowledge base search tools from the Support Agent AI over MCP, enabling MCP clients to handle customer support queries with grounded, citation-backed answers.