| name | mattermost-mcp-connector |
| description | MCP connector for Mattermost team communication – enables AI-powered message management, channel operations, and workflow automation through Claude |
| license | MIT |
| tags | ["dev","communication","mcp","mattermost","chat"] |
| difficulty | intermediate |
| time_to_master | 4-8 weeks |
| version | 1.0.0 |
Mattermost MCP Connector
Overview
This skill enables Claude to interact with Mattermost through the Model Context Protocol (MCP). It provides a bridge between Claude's AI capabilities and Mattermost's REST API, allowing natural language control of Mattermost operations, intelligent automation, and AI-powered assistance for Mattermost workflows.
When to Use This Skill
- Channel creation and management via AI
- Message summarization and thread digestion
- Slash command and bot creation
- Webhook and integration configuration
- User and team administration
Architecture
┌─────────────┐ ┌─────────────────┐ ┌──────────────────┐
│ Claude │────▶│ MCP Server │────▶│ Mattermost │
│ (Client) │◀────│ (TypeScript) │◀────│ (REST API )│
└─────────────┘ └─────────────────┘ └──────────────────┘
Core Concepts
MCP Server Setup
The connector implements an MCP server that exposes Mattermost operations as tools Claude can invoke. The server translates natural language intentions into REST API calls.
Key Endpoints/Interfaces
/api/v4/channels, /api/v4/posts, /api/v4/teams, /api/v4/users, /api/v4/webhooks
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: "mattermost-mcp-connector",
version: "1.0.0",
});
server.tool(
"list_resources",
"List and query Mattermost 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/v4/channels`, {
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": {
"mattermost-mcp-connector": {
"command": "node",
"args": ["path/to/mattermost-mcp-connector/index.js"],
"env": {
"MATTERMOST_API_KEY": "your-api-key",
"MATTERMOST_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 Mattermost 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 Mattermost API; sanitize outputs
- Logging: Log all API interactions for debugging and audit purposes
Example Prompts
"Summarize all unread messages in the #engineering channel and create action items"
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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