In-depth architectural comparison of the Humanforai MCP and Moxie Docs MCP MCP servers. Compare execution transports, security boundaries, tool capabilities, quality scores, and ready-to-paste client installation snippets for Claude, Cursor, Windsurf, and VS Code.
At a Glance & Executive Verdict
Humanforai MCP
Agreements & Coordination · Local stdio
Quality: 64/100 (Good) | Auth: No auth required
Moxie Docs MCP
Knowledge & Memory · Local stdio
Quality: 82/100 (Excellent) | Auth: API Key required
Verdict Summary: Choose Humanforai MCP if you need specialized Agreements & Coordination tools running via a local process. Choose Moxie Docs MCP if your workspace requires Knowledge & Memory integration with local subprocess execution. Both servers can be configured concurrently in your client's mcpServers manifest.
Which MCP Server Should You Choose?
Choose Humanforai MCP when:
You need dedicated capabilities in the Agreements & Coordination domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: No auth required (Free / Open Source).
Hire a real human operator for tasks that need physical presence, perception, or judgment: real-world verification, product testing, AI output review, data collection, and local errands. Remote streamable HTTP at https://humanforai.dev/mcp or local stdio via npx -y humanforai.
MCP & Agent Skills for Automated Documentation, and codebase conventions + context
Tools & Capabilities Breakdown
Humanforai MCP Tools (4)
get_human_services
Fetch the Human For AI manifest: available services, operator profile (location, languages, working hours), response times, accepted and rejected task types, and trust & safety policy. Call this first to decide whether and how to hire the human. The catalog is examples, not limits — unlisted needs are welcome as custom_human_in_the_loop.
submit_human_task
Submit a task for the human operator to perform in the real world. Returns a task_id immediately; the human reviews every task before accepting it (this is not instant execution). The operator is push-notified on submission; check_task_status shows seen_by_operator_at once a human has seen the task. Free during the pilot. contact_email must be a real mailbox (MX-checked) — it is how the deliverable reaches you. No mailbox? Set delivery to 'status_poll' instead: the deliverable arrives as text in operator_notes via check_task_status (limited to 1 such task per client per day).
check_task_status
Look up a submitted task by its task_id. Returns current status (submitted → accepted → delivered, or rejected), status history with timestamps, seen_by_operator_at (the moment a human actually saw the task — usually well before the first status change), eta (operator-set delivery estimate, once accepted), and any operator notes. Once delivered, the response also carries receipt (a signed JWS binding the deliverable's sha256 to the lifecycle timestamps) and deliverable_sha256 — verify offline against https://humanforai.dev/.well-known/jwks.json.
Ready-to-Paste Client Configurations
Paste either (or both) of these JSON server blocks into your client config file (e.g. claude_desktop_config.json or ~/.cursor/mcp.json).
Humanforai MCP is categorized under Agreements & Coordination and uses a local stdio subprocess. In contrast, Moxie Docs MCP belongs to Knowledge & Memory using local stdio subprocess. Select Humanforai MCP when you need capabilities focused on agreements & coordination and Moxie Docs MCP when you require tools for knowledge & memory.
Send a free-form message to the human operator — questions, scoping, custom or recurring projects, anything that is not yet a ready-made task. reply_to is REQUIRED (an email you or your principal can read); it is the only way the operator can answer.
Moxie Docs MCP Tools (12)
moxie.get_ai_context
Compact pre-edit briefing: repo status, verified commands, top conventions, open gaps, team notes. Read this first.
moxie.get_doc_impact
Given the paths you're about to change (and any you're deleting), returns the conventions, gaps, and existing docs whose evidence overlaps them - and flags net-new/undocumented surfaces.
moxie.get_api_context
Given paths you're about to touch, returns structured context for any API endpoints they map to: method, path, schema, and known consumers/features.
moxie.review_change
Self-review a change before opening the PR; returns a severity-ranked verdict (clean / warnings / must-fix) covering convention breaches, stale docs, undocumented surface, and broken references.
moxie.get_conventions
Discovered coding conventions, grouped by category, with confidence scores, agent guidance, and source-file citations.
moxie.search_docs
Semantic + keyword search over generated docs, conventions, gaps, and AI context.
moxie.get_doc_gaps
Unresolved documentation gaps with severity and the paths they concern.
moxie.get_documentation_opportunities
Recommended doc work: missing docs, drift repairs, and PR templates.
moxie.get_documentation_patterns
How the repository organizes and maintains its docs (where new docs belong).
moxie.list_docs
Paginated, section-grouped table of contents of every generated doc.
moxie.propose_doc_update
Add or update a doc as part of your current change; returns the target path + Markdown to write into your branch.
moxie.propose_doc_removal
Remove a Moxie-tracked doc your change makes obsolete; returns the path to delete in your branch.