PM Agent MCP Server
An MCP server that provides tools for product management tasks like backlog prioritization, feedback analysis, capacity assessment, and dependency mapping.
README
PM Agent MCP Server
Overview
MCP server with 4 tools to help Product Manager (Asha) make data-driven decisions.
The 4 Tools
1. prioritize_backlog
Ranks backlog items (1-35) by RICE scoring.
- Input: method, max_results, filters
- Output: Ranked items with flags (dependencies, stale, unestimated, no customer signal)
2. analyze_feedback
Extracts themes from 90 customer feedback entries.
- Input: group_by, sentiment_filter, bias_analysis flag
- Output: Themes with customer segments, bias warnings
3. assess_capacity
Calculates real team capacity for a sprint.
- Input: sprint_id, engineer names (optional)
- Output: Team capacity + per-engineer breakdown with warnings
- Formula Discovered:
available = (21 - pto_days × 2.1) × (allocation/100) - carry_over
4. map_dependencies
Maps dependency chains for backlog items.
- Input: item_ids, max_depth
- Output: Dependency graph, cycles detected, risk flags
Setup
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
python server.py
Data Path Contract
The server reads data from PM_AGENT_DATA environment variable:
export PM_AGENT_DATA=/path/to/data
python server.py
Falls back to ./data if env var not set.
Tools Usage
Each tool returns JSON with:
status: "success" or "error"data: Tool-specific outputmessage: Error details if status is "error"
Files
server.py- MCP server entry pointtools/- Tool implementationsdata/- Sample data for local testingrequirements.txt- Dependencies
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