bb-mcp MCP Server
nitsuah/bb-mcp
This Node.js-based Model Context Protocol (MCP) server provides a standardized interface for LLM clients to interact with the Blackboard Learn REST API via HTTP or stdio. Designed for educational developers and institutions, it implements a secure middleware layer for RBAC
claude mcp add agentrank -- npx -y agentrank-mcp-server Overview
nitsuah/bb-mcp is a TypeScript MCP server. This Node.js-based Model Context Protocol (MCP) server provides a standardized interface for LLM clients to interact with the Blackboard Learn REST API via HTTP or stdio. Designed for educational developers and institutions, it implements a secure middleware layer for RBAC
Ranked #82 out of 116 indexed tools.
Actively maintained with commits in the last week.
Ecosystem
Score Breakdown
1 stars → early stage
Last commit today → actively maintained
No issues filed → no history to score
1 contributor → solo project
No dependents → no downstream usage
42 weekly installs → early adoption
Weights: Freshness 25% · Issue Health 25% · Dependents 25% · Stars 15% · Contributors 10% · How we score →
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From the README
# blackboard-learn-mcp
A standalone [Model Context Protocol](https://modelcontextprotocol.io) server wrapping the Blackboard Learn REST API. Point any MCP-compatible client at it — Claude Desktop, Cursor, agent-board, or anything else — and get structured access to courses, grades, assignments, announcements, and more.
---
## Why standalone?
The integration logic lives here, not in the client. agent-board, Claude Desktop, and Cursor all connect the same way. Build it once, use it everywhere. Blackboard's own team could point internal tooling at this server without touching any frontend code.
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## Architecture
```
┌─────────────────────────────────────────────────┐
│ Any MCP Client │
│ (Claude Desktop · Cursor · agent-board · ...) │
└──────────────────────┬──────────────────────────┘
│ MCP Protocol (HTTP or stdio)
▼
┌─────────────────────────────────────────────────┐
│ blackboard-learn-mcp (th Read full README on GitHub → Get the weekly AgentRank digest
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