bots

150+ vertical AI expert bots as agent tools. $1 bots run on YOUR machine - your data stays yours.

Should I use this

Quality & Safety

A
Description quality
100%
Schema completeness
98%
Naming quality
96%
Poisoning risk
80%
Permission match
100%
Protocol compliance
100%

Findings (2)

  • HIGHTool poisoning patterns detected
  • MEDIUMTool description contains suspicious base64-like encoded stringin get_bot

Based on automated analysis of tool definitions and protocol compliance.

Context Cost

~799Tokens (tool definitions)
~754 BTypical response size
Moderate attention impact (0.62% of 128k context)

This is the approximate number of tokens consumed each time the server's tools are loaded into a model's context. Higher counts reduce the attention available for other tasks.

Install

One-Click Install

Add this to your `claude_desktop_config.json` file:

{
  "mcpServers": {
    "bots": {
      "url": "https://urbot.net/mcp"
    }
  }
}

Remote endpoints

https://urbot.net/mcpstreamable-http

What it can do

Tool inventory

Tools (5)

🟢 Read-only🟡 Write🔴 Delete⚪ Unknown
🟢list_bots(category)

List the URBot catalog of 150+ trained vertical AI expert bots with slug, name, tagline, category, and price tiers (most bots start at $1). Optionally filter by category (e.g. education, health, finance, legal, technology, outdoor, 3d-modeling, game-dev, 3d-printing, media). Use the returned slug with get_bot, chat_with_bot, or get_skill. URBot bots keep your data yours - each one is downloadable and runs locally.

Input Schema

{
  "type": "object",
  "properties": {
    "category": {
      "type": "string",
      "description": "Optional category filter, case-insensitive (e.g. \"education\")"
    }
  },
  "additionalProperties": false,
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢get_bot(slug)

Get the full card for one URBot bot by slug: name, tagline, pitch, price tiers, 6-axis capability radar (knowledge/practical/empathy/technical/creativity/safety, 0-100), knowledge topics, which bots it pairs with, and team synergy bonuses. Find slugs via list_bots or search_bots.

Input Schema

{
  "type": "object",
  "properties": {
    "slug": {
      "type": "string",
      "description": "Bot slug, e.g. \"chef\", \"professor\", \"medic\""
    }
  },
  "required": [
    "slug"
  ],
  "additionalProperties": false,
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟡chat_with_bot(slug, message, session_id)

Send a message to a live URBot expert bot and get its reply (with emotion metadata). Works without an account via the free preview (a few messages per bot per session); purchased bots or an URBOT_API_KEY lift the limits. Pass the returned session_id back in to continue the same conversation. Example slugs: chef, medic, professor, legal, hunter, blender.

Input Schema

{
  "type": "object",
  "properties": {
    "slug": {
      "type": "string",
      "description": "Bot slug, e.g. \"chef\""
    },
    "message": {
      "type": "string",
      "description": "Your message to the bot"
    },
    "session_id": {
      "type": "string",
      "description": "Session id from a previous reply, to continue that conversation"
    }
  },
  "required": [
    "slug",
    "message"
  ],
  "additionalProperties": false,
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🔴get_skill(slug)

Generate an agent-ready SKILL.md (agentskills.io-style YAML frontmatter + system prompt + capability profile) for one URBot bot. Drop the file into any SKILL.md-compatible agent (Claude Code, Cursor, Hermes, ...) to use the bot as a native skill. Uses the live URBot Factory persona endpoint when credentials are available, otherwise builds from the bundled catalog snapshot (marked in frontmatter).

Input Schema

{
  "type": "object",
  "properties": {
    "slug": {
      "type": "string",
      "description": "Bot slug, e.g. \"chef\""
    }
  },
  "required": [
    "slug"
  ],
  "additionalProperties": false,
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢search_bots(query)

Keyword-search the URBot catalog across bot names, taglines, categories, knowledge topics, and capability pitches. Returns the top matches with slug, name, category, price, and why they matched. Use this first when you know the task but not which expert bot to use (e.g. "sourdough", "tax deductions", "unreal engine blueprints", "knee pain").

Input Schema

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "Free-text keywords, e.g. \"meal prep nutrition\""
    }
  },
  "required": [
    "query"
  ],
  "additionalProperties": false,
  "$schema": "http://json-schema.org/draft-07/schema#"
}

Recommended Prompts

search_research
Search for information about [topic] using bots
Expected tools: search_bots
find_specific
Find [specific item] using bots
Expected tools: search_bots
retrieve_data
Get details about [item] from bots
Expected tools: get_bot
fetch_info
Fetch [information type] using bots
Expected tools: get_bot
list_items
List all [items] available in bots
Expected tools: list_bots

Community

Rate this Server

Evidence

Recent observations

verifiedversion not recorded5 tools
verifiedversion not recorded5 tools