Ask Human

Ask Human

masony817

Creates a markdown file-based workflow where AI can escalate questions to humans instead of making incorrect assumptions or hallucinating answers.

Enables escalation of questions to humans through a markdown file-based workflow that prevents hallucinations by providing direct human-in-the-loop responses for critical decisions like database passwords, API endpoints, or architectural choices.

150239 views11Local (stdio)

What it does

  • Ask humans questions when AI is uncertain
  • Log questions with context in markdown files
  • Watch for human responses and continue processing
  • Track question history with timestamps
  • Handle multiple concurrent questions
  • Prevent hallucinations through human verification

Best for

AI agents needing clarification on API endpoints or credentialsPreventing costly mistakes from AI false confidenceCode generation requiring human domain knowledgeCritical decisions that need human oversight
Zero configuration setupFile-based workflow for easy debuggingBuilt-in concurrency locks and limits

About Ask Human

Ask Human is a community-built MCP server published by masony817 that provides AI assistants with tools and capabilities via the Model Context Protocol. Ask Human adds human-in-the-loop responses to AI, preventing errors on sensitive tasks like passwords and API endpoints. It is categorized under productivity, developer tools.

How to install

You can install Ask Human in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

License

Ask Human is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

ask-human mcp πŸ§‘β€πŸ’»πŸ€πŸ€–

PyPI version License: MIT Python 3.8+ "Buy Me A Coffee"

stop your ai from hallucinating. gives it an escape route when confused instead of false confidence.

the pain

ai blurts out an endpoint that never existed

the agent makes assumptions that are simply not true and has false confidence

repeat x100 errors and your day is spent debugging false confidence and issues when you could simply ask a question

the fix

an mcp server that lets the agent raise its hand instead of hallucinating. feels like mentoring a sharp intern who actually asks before guessing.

agent β†’ ask_human()
⬇
question lands in ask_human.md
⬇
you swap "PENDING" for the answer
⬇
agent keeps coding

sample file:

### Q8c4f1e2a
ts: 2025-01-15 14:30  
q: which auth endpoint do we use?  
ctx: building login form in auth.js  
answer: PENDING

you drop:

answer: POST /api/v2/auth/login

boom. flow continues and hopefully the issues are solved.

why it's good

  • pip install ask-human-mcp β†’ done
  • zero config, cross-platform
  • watches the file, instant feedback
  • multiple agents, no sweat
  • locks + limits so nothing catches fire
  • full q&a history in markdown (nice paper-trail for debugging)

30-sec setup

pip install ask-human-mcp
ask-human-mcp

.cursor/mcp.json:

{
  "mcpServers": {
    "ask-human": { "command": "ask-human-mcp" }
  }
}

restart cursor and vibe.

how it works

  1. ai gets stuck β†’ calls ask_human(question, context)
  2. question logged β†’ appears in ask_human.md with unique ID
  3. human answers β†’ replace "PENDING" with your response
  4. ai continues β†’ uses your answer to proceed

the ai receives your answer and keeps coding!

config options (if you want them)

command line

ask-human-mcp --help
ask-human-mcp --port 3000 --host 0.0.0.0  # http mode
ask-human-mcp --timeout 1800               # 30min timeout  
ask-human-mcp --file custom_qa.md          # custom q&a file
ask-human-mcp --max-pending 50             # max concurrent questions
ask-human-mcp --max-question-length 5000   # max question size
ask-human-mcp --rotation-size 10485760     # rotate file at 10mb

different clients

cursor (local):

{
  "mcpServers": {
    "ask-human": {
      "command": "ask-human-mcp",
      "args": ["--timeout", "900"]
    }
  }
}

cursor (http):

{
  "mcpServers": {
    "ask-human": {
      "url": "http://localhost:3000/sse"
    }
  }
}

claude desktop:

{
  "mcpServers": {
    "ask-human": {
      "command": "ask-human-mcp"
    }
  }
}

what's in the box

  • zero configuration β†’ works out of the box
  • file watching β†’ instant response when you save answers
  • timeout handling β†’ questions don't hang forever
  • concurrent questions β†’ handle multiple ai agents
  • persistent logging β†’ full q&a history in markdown
  • cross-platform β†’ windows, macos, linux
  • mcp standard β†’ works with any mcp client
  • input validation β†’ size limits and sanitization
  • file rotation β†’ automatic archiving of large files
  • resource limits β†’ prevent dos and memory leaks
  • robust parsing β†’ handles malformed markdown gracefully

security stuff

  • input sanitization β†’ removes control characters and validates sizes
  • file locking β†’ prevents corruption from concurrent access
  • secure permissions β†’ files created with restricted access
  • resource limits β†’ prevents memory exhaustion and dos attacks
  • path validation β†’ ensures files are written to safe locations

limits (so nothing breaks)

thingdefaultwhat it does
question length10kbmax characters per question
context length50kbmax characters per context
pending questions100max concurrent questions
file size100mbmax ask file size
rotation size50mbsize at which files are archived

platform support

  • windows β†’ full support with native file locking
  • macos β†’ full support with fsevents file watching
  • linux β†’ full support with inotify file watching

api stuff

ask_human(question, context="")

ask the human a question and wait for response.

answer = await ask_human(
    "what database should i use for this project?",
    "building a chat app with 1000+ concurrent users"
)

other tools

  • list_pending_questions() β†’ get questions waiting for answers
  • get_qa_stats() β†’ get stats about the q&a session

development

from source

git clone https://github.com/masonyarbrough/ask-human-mcp.git
cd ask-human-mcp
pip install -e ".[dev]"
ask-human-mcp

tests

pytest tests/ -v

code quality

black ask_human_mcp tests
ruff check ask_human_mcp tests  
mypy ask_human_mcp

contributing

would love any contributors

issues

use the github issue tracker to report bugs or request features.
you can also just email me: [email protected]

include:

  • python version
  • operating system
  • mcp client (cursor, claude desktop, etc.)
  • error messages or logs
  • steps to reproduce

changelog

see CHANGELOG.md for version history.

license

mit license - see LICENSE file for details.

thanks

Alternatives

Related Skills

Browse all skills
ai-sdk

Answer questions about the AI SDK and help build AI-powered features. Use when developers: (1) Ask about AI SDK functions like generateText, streamText, ToolLoopAgent, embed, or tools, (2) Want to build AI agents, chatbots, RAG systems, or text generation features, (3) Have questions about AI providers (OpenAI, Anthropic, Google, etc.), streaming, tool calling, structured output, or embeddings, (4) Use React hooks like useChat or useCompletion. Triggers on: "AI SDK", "Vercel AI SDK", "generateText", "streamText", "add AI to my app", "build an agent", "tool calling", "structured output", "useChat".

6
crewai-developer

Comprehensive CrewAI framework guide for building collaborative AI agent teams and structured workflows. Use when developing multi-agent systems with CrewAI, creating autonomous AI crews, orchestrating flows, implementing agents with roles and tools, or building production-ready AI automation. Essential for developers building intelligent agent systems, task automation, and complex AI workflows.

2
godot

This skill should be used when working on Godot Engine projects. It provides specialized knowledge of Godot's file formats (.gd, .tscn, .tres), architecture patterns (component-based, signal-driven, resource-based), common pitfalls, validation tools, code templates, and CLI workflows. The `godot` command is available for running the game, validating scripts, importing resources, and exporting builds. Use this skill for tasks involving Godot game development, debugging scene/resource files, implementing game systems, or creating new Godot components.

732
cold-email

When the user wants to write, improve, or build a sequence of B2B cold outreach emails to prospects who haven't asked to hear from them. Use when the user mentions 'cold email,' 'cold outreach,' 'prospecting emails,' 'SDR emails,' 'sales emails,' 'first touch email,' 'follow-up sequence,' or 'email prospecting.' Also use when they share an email draft that sounds too sales-y and needs to be humanized. Distinct from email-sequence (lifecycle/nurture to opted-in subscribers) β€” this is unsolicited outreach to new prospects. NOT for lifecycle emails, newsletters, or drip campaigns (use email-sequence).

25
instagram-automation

Automate Instagram tasks via Rube MCP (Composio): create posts, carousels, manage media, get insights, and publishing limits. Always search tools first for current schemas.

21
youtube-automation

Automate YouTube tasks via Rube MCP (Composio): upload videos, manage playlists, search content, get analytics, and handle comments. Always search tools first for current schemas.

20