Persistent memory for AI coding agents (Cursor, Claude, Codex & others), served over MCP.

MCPedia

A knowledge base server for AI agents via the Model Context Protocol (MCP). MCPedia stores, searches, and manages reusable knowledge entries -- skills, rules, patterns, guides, and references -- accessible to AI coding agents like Cursor, Codex, Cursor, and others through the MCP standard.

Why MCPedia?

AI coding agents like Cursor, Cursor, and Codex are powerful -- but they forget everything between sessions. MCPedia gives them persistent memory. You teach your agent something once (a coding pattern, a project convention, a debugging trick) and it remembers it forever.

What can you do with it?

• Save knowledge -- capture coding patterns, project rules, style guides, or anything your agent should know
• Search & retrieve -- your agent can search by keyword, filter by language/domain/project, or pull entries by context
• Share across agents -- the same knowledge base works with any MCP-compatible agent, so switching tools doesn't mean starting over
• Stay in control -- lock the database when you don't want agents making changes, unlock it when you do

Think of it as a personal wiki that your AI agents can read and write to, automatically.

Core Concepts

Entries

Entries are the primary knowledge units in MCPedia. Each entry has:

• A unique slug (URL-safe identifier, e.g. rust-error-handling)
• A title and optional description
• Content in Markdown format (up to 32 KB)
• Kind classification: skill, rule, context, pattern, reference, or guide
• Optional metadata: language, domain, project
• One or more tags for categorization
• Automatic version tracking and timestamps

Example:

{
  "slug": "rust-error-handling",
  "title": "Rust Error Handling",
  "description": "Idiomatic error handling patterns in Rust",
  "kind": "skill",
  "language": "rust",
  "domain": "",
  "project": "",
  "tags": ["rust", "errors", "result"],