"markdown" matching MCP servers:

Enables querying and updating Markdown frontmatter metadata using DuckDB SQL, with optional semantic search capabilities for finding similar documents based on content.

A universal resource server that enables AI models to mount local folders, scrape web pages into Markdown, and query SQLite databases without writing code. It features a real-time TUI dashboard and persistent configuration for managing diverse knowledge sources.

A TypeScript MCP server for interacting with CDISC Define-XML 2.0 and 2.1 files, enabling users to load, search, and retrieve clinical data metadata including datasets, variables, and codelists. It supports local file processing with document caching and provides responses in both JSON and Markdown formats.

Integrates Redshift database query capabilities with vector-based knowledgebase tools for semantic search and RAG applications. It enables users to execute SQL queries, explore database schemas, and perform hybrid semantic searches on markdown files stored in S3.

Enables users to ask whether a company is still sponsoring H-1B visas and get markdown tables combining DOL LCA, PERM and USCIS approval/denial data, with six-month trends versus a year earlier and green-card signals per employer. Also supports comparing companies, finding top sponsors by role and location, salary ranges, and disambiguating employer entities, all running locally and offline.

Exposes SQLite database query tools and markdown document resources over JSON-RPC 2.0 stdio transport, enabling AI assistants to read and search documents and execute read-only SQL queries.

Celp-MCP enables natural-language analytics over SQL, MongoDB, and Databricks warehouses through MCP-compatible clients, converting questions into multi-step database plans and returning markdown reports.

Minimizes LLM token consumption via YAML serialization, HTML-to-Markdown distillation, and pre-flight token counting, with tools for web content extraction and metrics database querying.

Exposes an Oracle database to MCP clients over stdio, offering 75 tools to query, modify, inspect, and triage the database with zero-install thin mode requiring no Oracle Client. Every statement is recorded in a Markdown audit log.

A graph-friendly relational server that stores project memory, tasks, and metadata in a centralized SQLite database as the authoritative source of truth. It enables AI agents to manage complex project states through entity-relationship modeling and can generate human-readable markdown views on demand.

Enables querying and formatting Loki logs from Grafana via the Model Context Protocol. It supports LogQL queries, label retrieval, and provides results in text, JSON, or markdown formats.

Enterprise MCP server that exposes multiple MySQL databases to AI services through one endpoint, with API-key auth, per-key database scoping, a layered SQL guard, and a markdown schema-knowledge graph.

Zero-config knowledge base for AI coding agents. Loads your markdown docs into a searchable database and exposes them as MCP tools — search, read, and manage documentation without leaving your editor. Works instantly with SQLite (no setup), upgrades to PostgreSQL + pgvector for hybrid semantic search. 6 MCP tools, 3 resources, FTS5 keyword search, 176 tests.

Enables AI assistants to manage personal finances through natural language, including adding, editing, listing, and deleting expenses, organizing them into categories, and setting monthly budgets with overspend warnings. It also provides spending summaries with month-over-month comparisons, budget status checks, and exportable Markdown or CSV reports, all backed by PostgreSQL storage with Google OAuth-authenticated per-user accounts.

An MCP server that provides data bridging from Spring Boot interfaces and a lightweight Python sandbox for script execution. It enables agents to fetch data as Markdown or Parquet files and perform automated data analysis within a controlled environment.

MCP server for publishing markdown AI research entries to a Convex database. Supports both development and production environments with secure deployment credentials.

Enables users to document data and connect it to AI agents by defining tools and instructions in markdown files. It supports building RAG and text-to-SQL applications that can be deployed as MCP servers, APIs, or CLIs.

Lets Claude or any MCP client query a Neo4j index of a markdown vault, answering what is connected to a note and how far, how two notes relate, which notes are orphans or dangling links, and running read-only Cypher.

Stores markdown knowledge notes in SQLite or Postgres and exposes them to AI agents over MCP, letting agents read individual sections, search, and write updates transactionally. Each write is validated, and anything that introduces broken links, missing summaries, or duplicate text is rolled back with a reason.

Lets Claude Desktop, Claude Code, and other MCP clients map the structure of a SQLite database and run read-only SQL queries against it, returning compact Markdown results. Multi-layered protections make any write impossible, so a database can be explored without reviewing each query first.