pm-agents
Enables reading emails for morning briefing generation.
Provides read-only access to Jira analytics for metrics agent and allows creating Jira tickets through the prd_ticket agent.
Supports writing morning briefings and end-of-day dumps into daily notes, and creating PRDs via the prd_ticket agent.
Powers grounded Q&A and note upkeep over a local Obsidian vault using a RAG index.
Enables read-only access to PostHog analytics for metrics and briefing agents.
Integrates with Slack for sending morning briefings and end-of-day dumps.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@pm-agentsgive me my morning briefing"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
pm-agents
A multi-agent product-management copilot that automates a PM's operating rhythm: morning briefings, metrics answers, grounded knowledge lookups over an Obsidian vault, and PRD/ticket drafting — each a specialised backend agent with real integrations and hard guardrails.
Built and used daily by a working product manager. Runs locally on Windows against a Claude subscription (no per-token API billing) by driving the logged-in claude CLI in print mode, with tools exposed as a local stdio MCP server.
Agents
A single-agent orchestrator (all tools) plus four specialists:
Specialist | Does | External creds |
| Vault Q&A grounded in a local RAG index; guarded note upkeep | none (local only) |
| PostHog + Jira analytics, anomaly/OKR watch (read-only) | PostHog, Jira |
| Morning briefing + EOD dump written into the daily notes | Jira, Slack, Notion, PostHog, Gmail |
| Draft + create PRDs (Notion) and Jira tickets, on confirmation | Notion, Jira |
Related MCP server: MCP GitHub Project Manager
Architecture notes
Print-mode + MCP, not the streaming SDK. The Agent SDK's streaming stdio transport does not complete its control handshake with the native
claude.exeon Windows (verified: hangs on initialize).claude -pworks reliably, so the runner drives that directly and exposes the Python tools via--mcp-configpointing atpm_agents.mcp_server. Pragmatism over purity.Allowlist-only tool execution. Tools are pre-approved through an explicit
--allowedToolsallowlist plus--strict-mcp-config— no blanket permission bypass. Each specialist gets the minimum tool set for its job.Guardrails in code, not prompts (
pm_agents/guardrails.py): production-database references are hard-blocked by regex before any tool executes; write operations require explicit confirmation. The model is never trusted to self-police.Grounded-only answers. The knowledge agent must quote retrieved chunks; if retrieval returns nothing it says so instead of improvising.
One agent, one prompt file. Each agent's behaviour lives in a single markdown file under
pm_agents/prompts/— reviewable, diffable, no prompt spaghetti.Scheduling: Windows Task Scheduler entries (
scripts/schedule_tasks.ps1) drive the morning/EOD/weekly runs.
Setup
python -m venv .venv && .venv/Scripts/activate
pip install -r requirements.txt
cp .env.example .env # fill in your own tokens — nothing is committed
python scripts/smoke_test.pyLayout
pm_agents/
agents/ # the four specialists
integrations/ # jira, notion, slack, gmail, posthog clients (thin, typed)
prompts/ # one behaviour file per agent
tools/ # vault + RAG tools
guardrails.py # hard safety checks (prod-DB block, allowlists)
mcp_server.py # stdio MCP server exposing the tools
scripts/ # entrypoints: morning brief, EOD, weekly, chat, diagnosticsThis server cannot be deployed
Maintenance
Related MCP Connectors
Project management for AI agents: tasks, docs, decisions and time in one shared team context.
- DartOAuthcom.dartai
AI-native project management for tasks, docs, collaboration, and agents.
AI-native project management + agent memory: tasks, sprints, risk, burnout, knowledge search.
- RevelicaOAuthcom.revelica
Product intelligence for AI agents — query a Revelica workspace's ideas, specs, and research.
Related MCP Servers
- FlicenseNot gradedqualityBmaintenanceProvides a local, agent-maintained product context layer over MCP, serving structured strategy, competitor, customer feedback, and feature inventory data to any AI tool such as Claude, Cursor, or ChatGPT, with local data storage, bring-your-own-LLM support, and weekly evidence-based roadmap reviews that can sync suggestions to Jira or Linear.-
- AlicenseNot gradedqualityAmaintenanceTurns GitHub Projects v2 into an agentic project-management substrate where AI coding agents register, atomically claim tasks, send heartbeats, review each other's work, and stay within token budgets, while also offering AI-powered PRD generation, task breakdown, sprint planning, and triage. Everything is stored in GitHub issues, project fields, and comments, so no external database or infrastructure is required.95 npmMIT
- AlicenseNot gradedqualityAmaintenanceTurns GitHub Projects v2 into an agentic project management layer where AI coding agents self-assign tasks, coordinate via heartbeats, submit work for review, and stay within token budgets. It also provides AI-powered PRD generation, sprint planning, issue triage, and a PRD-to-issues pipeline, all backed by GitHub-native storage with no external infrastructure.95 npmMIT
- AlicenseNot gradedqualityAmaintenanceEnables AI agents and project managers to turn GitHub Projects v2 into an autonomous project management platform with task checkout, multi-agent coordination, PRD-to-issue pipelines, sprint planning, triage, and GitHub-native storage.95 npmMIT