What it is
MCP, the Model Context Protocol, is an open standard published by Anthropic in November 2024. It defines a JSON-RPC interface that AI assistants (clients) use to talk to outside systems (servers) — your filesystem, a database, a meeting library, a calendar — without each side knowing anything specific about the other.
A useful analogy: MCP is to AI assistants what USB-C is to laptops. Before USB-C, every device had its own connector. After it, one cable works everywhere. MCP plays the same role for tool integrations.
Why it matters for end users
If you’ve ever wanted Claude or ChatGPT to do something with a specific app — read your meeting notes, query a private database, search your codebase — you needed someone to build a custom integration. With MCP, that work happens once, server-side, and every MCP-compatible chat client gets it for free.
Concretely, that means:
- You set up the MCP server for the tool you care about — for hosted servers (like Granola’s), through a settings or OAuth flow inside the chat client; for local servers (like Gistlist’s), by adding an entry to the client’s config file (e.g.
claude_desktop_config.json). - You connect your chat client to it.
- The assistant can now answer questions and take actions that involve that tool, with no copy-paste.
It’s the same shift that browser extensions enabled for the web: the assistant becomes useful for your data, not just generic web knowledge.
Examples of MCP-enabled tools
Anthropic’s reference server collection and community catalogs together cover a wide range of integrations. A few public examples:
- Filesystem — let Claude read and write files in a folder you choose.
- GitHub — query repos, issues, and pull requests through Claude.
- Slack — search and post to your workspace.
- Postgres / SQLite — query a database in natural language.
- Gistlist — search across your local meeting library and pull the relevant transcripts into the conversation. (See /notes/founder-one-on-ones for a worked example.)
Many MCP servers — including Gistlist’s — run as local subprocesses on your machine, communicating over stdio. Others, like Granola’s, are hosted on the vendor’s infrastructure and reached via remote HTTP. Both patterns are part of the spec; which one a given server uses determines where your data flows.
How MCP differs from plugins, extensions, and APIs
It’s easy to mistake MCP for the latest in a long line of integration mechanisms. The substantive difference is where the contract lives.
| Mechanism | Contract is between… | Reusable across clients? |
|---|---|---|
| Custom API integration | The app and one specific client | No |
| Browser extension | The browser and one website/feature | No (browser-locked) |
| ChatGPT plugin (deprecated) | OpenAI and the plugin author | No (OpenAI-only) |
| MCP server | Any MCP client and any MCP server | Yes |
The reusability is the point. A single Gistlist MCP server works with Claude Desktop today and with any future client that adopts the spec — no extra integration work.
Using MCP with Gistlist
Gistlist ships an MCP server that exposes three tools to Claude Desktop: list_recent_meetings, search_meetings, and get_meeting. Claude can use them to answer questions across your whole meeting history — “what did we decide in the Acme onboarding retro?”, “who have I met with this month?” — without you copying transcripts into the chat. Setup is a config-file edit; details are in the Claude Desktop integration docs.
The fit is natural: Gistlist already keeps every meeting as plain markdown on your disk, so there’s no separate import or sync step to a Gistlist-hosted service. The local MCP server reads the on-disk index and returns the meetings Claude asks for; that selected content does become part of Claude’s conversation context, since that’s how Claude answers your question.
Further reading
If you’re comparing meeting tools that integrate with Claude, Granola vs Gistlist walks through how the two products differ — including how each one handles MCP.
If you want a concrete workflow, Tracking founder 1:1s without a CRM shows what asking Claude across an MCP-connected meeting library actually looks like in practice.