"Markdown" matching MCP servers:

A Model Context Protocol server that converts Markdown content to HTML format.

A multi-agent research system that decomposes complex queries into targeted sub-questions, searches the web in parallel, scores source credibility, and synthesizes findings into structured markdown reports.

Email for AI agents. Send and receive as markdown with human oversight.

A memory system for AI agents that maintains a human-readable, typed Markdown knowledge base with an always-in-context index, enabling recall, correction, and trust decay through MCP.

Simulate hundreds of AI agents to predict how communities react to events and policies. Upload any document (PDF, Markdown, text) and DeepMiro spawns a diverse swarm of AI agents that debate, share, and form opinions — then delivers a calibrated prediction report. Free and open-source.

Provides a hybrid memory architecture with a thin SQLite index and Markdown cold storage, enabling AI agents to write, query, link, and rebuild long-term memories via MCP tools, model-agnostic and zero third-party dependencies.

Enables AI clients to perform autonomous multi-agent deep research through MCP tools, including deep research, quick search, and retrieval of archived Markdown reports with live web search and source citations.

Local-first working-state checkpoints and portable handoff packets for AI coding agents. Continuation checkpoints recover Claude Code sessions after rate limits, crashes, and compaction; packets hand tasks across tools, repos, and machines — Markdown on disk, no cloud, no telemetry.

Manages an agent's long-term memories as versioned markdown files with searchable SQLite indexes, supporting lifecycle states, conflict-gated recall, revision, and explicit forgetting without automatic deletion.

Enables the creation and execution of task-specific AI sub-agents defined in markdown across any MCP-compatible tool like Cursor or Claude Desktop. It integrates with execution engines such as Claude Code, Cursor CLI, and Gemini CLI to provide portable and reusable specialized agent workflows.

Enables AI agents to interact with issue, comment, document, and agent workflows through a simplified HTTP API, returning compact Markdown or file-based snapshots.

Gives AI coding agents persistent, searchable typed memory stored as plain markdown files, allowing them to record decisions, contracts, tasks, evaluations, and session logs and update entries by id.

Enables users to create and refine a research outline, queue report generation in the background, and retrieve progress or completed Markdown reports, with automatic checkpointing so unfinished work can resume after a restart.

Enables AI agents to manage hierarchical memory with Markdown-based storage, tiered architecture (L0-L3), and hybrid retrieval for transparent and persistent context.

Enables AI assistants to run complete website tasks in a real browser, returning every step, the final markdown content, and persistent tabs for follow-up calls or concurrent tasks.

A context preservation engine for AI agents that bundles project state into a markdown package and syncs it to clipboard or cloud, enabling zero knowledge loss across sessions.

Agent Toolbelt is an MCP server exposing 11 focused API tools for LLM agents — schema generation, text extraction, token counting, CSV conversion, Markdown conversion, URL metadata, regex builder, cron expressions, address normalization, color palettes, and brand kits. Each tool is a focused microservice with structured input/output, WCAG-scored color data, USPS address parsing, and multi-model to

Service-boundary-aware document exchange center for coordinating heterogeneous LLM code agents via MCP. Versioned Markdown store, pub-sub notifications, and diff-aware update protocol.

Enables an agent to fan out a build into independent targets, each run by a headless coding agent in its own git worktree and gated by a shell-free kill check that must print an exact line. Exposes tools to validate requests, launch and track runs, inspect lane status, cancel or recover runs, and produce review-ready markdown reports, without ever merging or pushing.

Persistent memory for AI agents built on the LLM Wiki pattern: a plain-Markdown brain (also a valid Obsidian vault) with SQLite metadata, local semantic search via fastembed (no API keys), one-call session context with project auto-detection, and a decision log with rationale. Works with Claude Code, Claude Desktop, Cursor, and any MCP client.