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zulip-mcp

An MCP server that gives Claude access to your Zulip channels, so you can ask for summaries of recent activity.

Setup

1. Get your Zulip API key

  1. In Zulip, go to Settings → Account & privacy → API key

  2. Click Generate API key and copy it

2. Create a .zuliprc file

Copy the example file and fill in your credentials:

cp .zuliprc.example .zuliprc

Then edit .zuliprc with your email and API key:

[api]
key=your_api_key_here
email=your_email@recurse.com
site=https://recurse.zulipchat.com

Alternatively, Zulip can generate a pre-filled .zuliprc for you: Settings → Account & privacy → API key → Show/change your API key → Download .zuliprc. Place the downloaded file in the project directory.

3. Configure your channels

Edit config.yaml to set the channels you want in your default digest and how far back to look:

zuliprc: .zuliprc

defaults:
  hours_back: 24
  channels:
    - general
    - announcements
    - your-interests

Use exact stream names as they appear in Zulip.

Related MCP server: Telegram MCP Server

🛡️ Architecture & Data Privacy

This is a standard MCP server. It is LLM-agnostic and can be used with any MCP-compatible client. The privacy of your Zulip data depends entirely on the client you choose:

  • Cloud Clients (e.g., Claude Desktop): Data will be sent to the provider's servers for processing.

  • Local Clients (e.g., Ollama + local MCP host): Data stays on your machine. If you are using this in a community with high privacy expectations, consider using a local-only workflow.

4. Claude Install

If you're using Claude Code, you can have Claude handle steps 4 and 5 for you. Open Claude Code in the project directory and paste this prompt:

"Install dependencies for this project and register it as an MCP server in my Claude Code settings."

5. Install dependencies (manual)

uv sync

6. Add to Claude Code (or Claude Desktop) (manual)

Claude Code — run from the project directory:

claude mcp add zulip-mcp -- uv run --project /absolute/path/to/zulip zulip-mcp

This writes the server into ~/.claude/settings.json. To scope it to this project only, add it manually to .claude/settings.json (committed) or .claude/settings.local.json (local only) in the project root:

{
  "mcpServers": {
    "zulip-mcp": {
      "command": "uv",
      "args": ["run", "--project", "/absolute/path/to/zulip", "zulip-mcp"]
    }
  }
}

Claude Desktop — add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "zulip-mcp": {
      "command": "uv",
      "args": ["run", "--project", "/absolute/path/to/zulip", "zulip-mcp"]
    }
  }
}

Note: The server reads config.yaml from the project directory by default. You can override this with the ZULIP_MCP_CONFIG environment variable:

{
  "mcpServers": {
    "zulip-mcp": {
      "command": "uv",
      "args": ["run", "--project", "/absolute/path/to/zulip", "zulip-mcp"],
      "env": {
        "ZULIP_MCP_CONFIG": "/absolute/path/to/config.yaml"
      }
    }
  }
}

Usage

Once the MCP is connected, you can ask things like:

  • "Summarize what's been discussed in #general today"

  • "Give me a digest of all my configured channels"

  • "What topics came up in #announcements in the last 48 hours?"

  • "List my subscribed channels"

To protect user privacy, pass anonymize=true to any tool that returns message content. Real names will be replaced with stable aliases ({User1}, {User2}, etc.) before anything is sent to Claude:

  • "Summarize the checkins channel from the last 24 hours. Use anonymize=true for all tool calls."

The alias mapping is saved locally at ~/.config/zulip_mcp/anonymizer_map.json for de-anonymization after the fact.

Privacy-first CLI: prompt_with_privacy.py

For a workflow that anonymizes messages before sending to the LLM and deanonymizes the response, use the included script. It sends your query to the LLM with anonymization enforced, then automatically de-anonymizes the response using the local alias map before writing the result to a file.

python prompt_with_privacy.py "your query here"

⚠️ Privacy & Security Disclosure

Please be aware of the following before using it in a community setting (like the Recurse Center):

  • Data Processing: By default, the prompt_with_privacy.py script sends Zulip message content to Anthropic's servers for processing. Even when using the anonymize=true flag, users may still be identifiable through writing patterns, specific interests, or context (stylometry).

  • Consent: Consider getting the consent of all participants before using this tool to summarize any non-public Zulip channels.

  • Local Alternative: If you require 100% data privacy, it is recommended to modify the client to point to a local LLM (e.g., via Ollama or an internal cluster like RC's Heap) rather than using a cloud-based provider.

Options:

Flag

Default

Description

--output, -o

output.md

Path to write the de-anonymized response

Example:

python prompt_with_privacy.py "summarize checkins from the last 24 hours. return a one sentence summary for every person." --output checkins.md

The script:

  1. Appends "Use anonymize=true for all tool calls." to your prompt

  2. Invokes claude -p with the Zulip MCP and no other tools

  3. Replaces all {UserN} aliases in the response with real names

  4. Writes the result to the output file

Note: Requires claude to be available in your PATH and the zulip-mcp server registered in ~/.claude.json for this project directory (see setup steps above).

Local LLM CLI: zulip_local.py

For a fully local workflow that keeps all Zulip data on your machine, use the included script. It connects directly to a local Ollama instance (or any OpenAI-compatible endpoint) and runs the full agentic loop — fetching messages and summarizing them — without sending anything to a cloud provider.

1. Install Ollama

Download and install from ollama.com, or on macOS:

brew install ollama

2. Download a model

ollama pull gemma4:e4b

Any model that supports tool calling will work. gemma4:e4b is the default.

3. Start the Ollama server

ollama serve

Or run it as a background service via Homebrew (starts automatically on login):

brew services start ollama

Either way, the server listens at http://localhost:11434.

4. Run the script

uv run python zulip_local.py "summarize the checkins channel from the last 24 hours"

Configuration

Environment variable

Default

Description

ZULIP_MCP_MODEL

gemma4:e4b

Model to use

ZULIP_MCP_DIR

Script directory

Path to the zulip-mcp project

OPEN_WEBUI_API_KEY

Set to use Open WebUI instead of local Ollama

OPEN_WEBUI_BASE_URL

Base URL for Open WebUI (required with OPEN_WEBUI_API_KEY)

Both OPEN_WEBUI_API_KEY and OPEN_WEBUI_BASE_URL must be set to switch away from local Ollama.

CLI flags

Flag

Description

--model <name>

Override the model (takes precedence over ZULIP_MCP_MODEL)

--verbose

Print tool calls and raw tool results

Example:

uv run python zulip_local.py "summarize the checkins channel from the last 24 hours. give a one to two sentence summary for every person." --model llama3.2

Available tools

Tool

Description

list_channels

List all channels you're subscribed to

get_channel_messages

Fetch recent messages from one channel

get_checkins

Fetch check-ins one topic at a time (avoids context overload)

get_digest

Fetch messages from all configured channels at once

get_full_message

Fetch the complete content of a single message by ID

set_interests

Save your interests to config.yaml to filter digests

All tools that return message content accept an optional anonymize parameter (default: false).

You can override defaults inline — e.g. "summarize #checkins for the last 3 days" will pass hours_back: 72 to the tool.

Notes

  • Messages longer than 500 characters are truncated in digest/channel views. Truncated messages include their ID and a note, so Claude can call get_full_message to retrieve the complete content when it seems relevant.

  • The server fetches up to 1000 messages per channel per request.

  • .zuliprc contains your API key — don't commit it. It's in .gitignore by default.

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