About HumanHours
HumanHours is a hosted MCP server for tracking AI agent ROI and enriching company labour-cost data. It is for teams measuring saved time and money, with reporting and company enrichment available through an account-based remote connection.
Key features
- 01Record agent task events and calculate savings
- 02View ROI summaries and trend reports
- 03Group saved time and costs by agent or task
- 04Compare agents on a leaderboard
- 05Enrich companies with roles and wage data
- 06Run and check bulk enrichment jobs
Use cases
- 01Measure hours and money saved by agents
- 02Compare ROI across agents and task types
- 03Estimate labour costs from a company domain
- 04Enrich a list of company domains in bulk
MCP support
The remote MCP server exposes event logging, ROI reporting, usage, agent and task lists, and company enrichment tools. It connects over Streamable HTTP using OAuth 2.1 with PKCE; no local installation or manually copied API keys are needed.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://mcp.humanhours.dev/mcpclaude mcp add --transport http dev-humanhours-humanhours https://mcp.humanhours.dev/mcp{"mcpServers":{"dev-humanhours-humanhours":{"type":"http","url":"https://mcp.humanhours.dev/mcp"}}}Open in Cursor{"servers":{"dev-humanhours-humanhours":{"type":"http","url":"https://mcp.humanhours.dev/mcp"}}}Open in VS Code{"mcpServers":{"dev-humanhours-humanhours":{"type":"http","url":"https://mcp.humanhours.dev/mcp"}}}{"mcpServers":{"dev-humanhours-humanhours":{"serverUrl":"https://mcp.humanhours.dev/mcp"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
Tools
Details
From the project README
HumanHours MCP Server
Every agent, measured in human hours.
humanhours.dev ·
MCP docs
Track agent ROI and enrich companies straight from any MCP client. HumanHours is a remote, hosted MCP server: connect once with your HumanHours account and your agents can log task events, read what they saved, and pull real labour-cost data for any company.
No installation, no API keys to copy around, no local process to run.
Connect
| Endpoint | https://mcp.humanhours.dev/mcp |
| Transport | Streamable HTTP |
| Auth | OAuth 2.1 (PKCE) — browser login with your HumanHours account, approve workspace access |
Add it to any client that supports remote MCP servers (Claude Desktop, claude.ai, Cursor, and others). On first use you complete a browser login and approve the scopes below; the client stores a token, so there are no keys to manage by hand.
Claude Desktop / claude.ai
Add a remote connector pointing at https://mcp.humanhours.dev/mcp and complete the
login when prompted.
Cursor / other clients
{
"mcpServers": {
"humanhours": {
"url": "https://mcp.humanhours.dev/mcp"
}
}
}
Tools
Logging
track_event— Record one agent task event and compute the hours and money it saved.
Reading
get_summary— Aggregated ROI for a period, with a daily trend.time_saved_report— Hours saved, grouped by agent, task type, model, client, or time.cost_saved_report— Money saved, grouped the same ways.leaderboard— Top agents by a chosen metric.get_usage— Event usage against the plan's included quota.list_agents— Agents tracked, with 30-day hours and money saved.list_task_types— Built-in plus custom task types.
Enrichment
enrich_company— Turn a domain into roles, per-hour wages, and an annual labour-cost case.get_company— Read one enriched company from the library.list_companies— List the workspace's company library, optionally by tag.bulk_enrich— Queue a background job for many domains; returns a job id.get_job— Check the status of a bulk enrichment job.
Scopes
| Scope | Grants |
|---|---|
track:write | Log task events |
read:reports | Read ROI summaries, reports, leaderboards, usage |
enrich:write | Enrich companies and read the company library |
Docs
Full connection guide, scopes, and tool reference: https://humanhours.dev/docs/mcp
About
HumanHours is the ROI meter for AI agents: it measures the hours and money your agents save, and enriches companies with real wage data so every saving is grounded in what the work actually costs. Learn more at https://humanhours.dev.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.