| name | zulip-mcp-connector |
| description | MCP connector for Zulip threaded chat – enables AI-powered topic management, message organization, and team communication through Claude |
| license | Apache 2.0 |
| tags | ["dev","communication","mcp","zulip","chat"] |
| difficulty | intermediate |
| time_to_master | 4-8 weeks |
| version | 1.0.0 |
Zulip MCP Connector
Overview
This skill enables Claude to interact with Zulip through the Model Context Protocol (MCP). It provides a bridge between Claude's AI capabilities and Zulip's REST API, allowing natural language control of Zulip operations, intelligent automation, and AI-powered assistance for Zulip workflows.
When to Use This Skill
- Stream and topic management via AI
- Thread summarization and action extraction
- Bot development and webhook integration
- Message search across topics and streams
- User group and permission management
Architecture
┌─────────────┐ ┌─────────────────┐ ┌──────────────────┐
│ Claude │────▶│ MCP Server │────▶│ Zulip │
│ (Client) │◀────│ (TypeScript) │◀────│ (REST API )│
└─────────────┘ └─────────────────┘ └──────────────────┘
Core Concepts
MCP Server Setup
The connector implements an MCP server that exposes Zulip operations as tools Claude can invoke. The server translates natural language intentions into REST API calls.
Key Endpoints/Interfaces
/api/v1/streams, /api/v1/messages, /api/v1/users, /api/v1/events, /api/v1/user_groups
Implementation
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import { z } from "zod";
const server = new McpServer({
name: "zulip-mcp-connector",
version: "1.0.0",
});
server.tool(
"list_resources",
"List and query Zulip resources with optional filters",
{
query: z.string().optional().describe("Search query or filter"),
limit: z.number().optional().describe("Max results to return"),
},
async ({ query, limit }) => {
const response = await fetch(`${BASE_URL}/api/v1/streams`, {
headers: { "Authorization": `Bearer ${API_KEY}` },
});
const data = await response.json();
return {
: [{ : , : .(data, , ) }],
};
}
);
server.(
,
,
{
: z.().(),
: z.({}).().().(),
},
({ name, config }) => {
response = (, {
: ,
: {
: ,
: ,
},
: .({ name, ...config }),
});
data = response.();
{
: [{ : , : }],
};
}
);
server.(
,
,
{
: z.().(),
: z.().().(),
},
({ , timeframe }) => {
response = (, {
: { : },
});
data = response.();
{
: [{ : , : .(data, , ) }],
};
}
);
transport = ();
server.(transport);
Claude Desktop Configuration
{
"mcpServers": {
"zulip-mcp-connector": {
"command": "node",
"args": ["path/to/zulip-mcp-connector/index.js"],
"env": {
"ZULIP_API_KEY": "your-api-key",
"ZULIP_BASE_URL": "https://your-instance-url"
}
}
}
}
Best Practices
- Authentication: Store API keys securely using environment variables; never hardcode credentials
- Rate Limiting: Implement request throttling to respect Zulip API rate limits
- Error Handling: Provide clear, actionable error messages for common failure scenarios
- Pagination: Handle paginated responses for large datasets efficiently
- Caching: Cache frequently accessed read-only data to reduce API calls
- Security: Validate all inputs before passing to the Zulip API; sanitize outputs
- Logging: Log all API interactions for debugging and audit purposes
Example Prompts
"Summarize all topics in the #design stream from the last week and identify open decisions"
Security Considerations
- All API credentials must be stored as environment variables
- Implement input validation and sanitization for all tool parameters
- Use HTTPS for all API communications
- Follow the principle of least privilege for API token permissions
- Audit log all write operations for compliance tracking
Resources
Changelog
| Version | Date | Changes |
|---|
| 1.0.0 | 2026-04-01 | Initial MCP connector skill |
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