Tendem MCP server MCP Server
io.github.Toloka/tendem-mcp
Delegate research, writing, analysis, and data work to vetted human experts directly from your AI assistant.
What is the Tendem MCP server MCP server?
The Tendem MCP server connects your AI assistant to vetted human experts for judgment-heavy tasks like research, competitive analysis, copywriting, design review, and data cleaning. It handles the full lifecycle—task creation, scoping, approval, and result delivery—with transparent pricing and verified outputs. Ideal for founders, creators, and operators who need reliable expert work without managing freelancers.
Tendem extends your AI's capabilities by providing direct access to vetted human experts for complex, judgment-heavy work. You submit tasks in plain English, Tendem scopes the work and provides a transparent quote, and verified results come back as files, reports, or structured outputs. The MCP server integrates seamlessly into Claude, Cursor, GitHub Copilot, ChatGPT, Gemini CLI, and other MCP-compatible clients, with built-in polling, spend safety, and task management.
How to install Tendem MCP server
Copy-paste configuration for popular MCP clients.
Tools & capabilities
Tools this server exposes to the agent.
create_task— Submit a new task to Tendem with a plain-English descriptionget_task— Retrieve details about a specific taskget_contract— Get the scoped contract and pricing for a taskget_task_result— Fetch the verified result of a completed tasklist_tasks— List all your tasks with their current statusapprove_task— Approve and trigger payment for a task (gates spending)cancel_task— Cancel a task before approvalsend_message— Send a message to clarify task scope or answer expert questionsread_chat— Read messages and clarifications in the task chatget_account— Check your account balance and top-up statusget_file_upload_url— Get a URL to upload files for a task
Use cases
- Delegate competitive research or market analysis while your AI agent continues other work
- Submit copywriting or editing tasks and receive polished, verified content back into your chat
- Outsource data cleaning, structuring, or validation without leaving your AI workflow
- Get design or technical review from experts on work your agent has produced
- Build automated pipelines that create tasks, negotiate scope, and collect results with spend controls
Tendem MCP server MCP server FAQ
Tendem is a service that connects you to vetted human experts for judgment-heavy work—research, writing, analysis, design review, data cleaning. The MCP server lets your AI assistant submit tasks, track progress, and fetch results without leaving the chat.
No. Tendem charges per task based on scope and complexity. You set up an account at agent.tendem.ai, top up your balance, and approve tasks before they incur charges. The `approve_task` tool is what triggers payment, so you control spending.
In Claude Code or Cursor, run `/plugin marketplace add Toloka/tendem-mcp` then `/plugin install tendem@tendem-mcp`. For other clients (ChatGPT, GitHub Copilot CLI, Gemini), see the README for client-specific install commands. You'll authenticate via OAuth on first use.
For interactive use (Claude, Cursor, etc.), OAuth handles authentication automatically. For headless or CI pipelines, you can create an API key at agent.tendem.ai/mcp under the Agent builders tab and use it with mcp-remote or langchain-tendem.
Tendem scopes the work, provides a transparent quote, and waits for your approval. Once approved, experts work on it. The MCP server includes a background watcher that polls for updates and notifies you when the task needs input or is ready. You fetch results with `get_task_result`.
Yes. Use the eleven MCP tools (create_task, get_task, approve_task, etc.) to build your own workflow. For Python/LangChain, use langchain-tendem for simpler integration. Always check `get_account` before approving to ensure sufficient balance.
README (reference)
Source of truth, from the repository.
Tendem MCP
Delegate tasks to vetted human experts — straight from your AI assistant. 🧑🔬🤝🤖
Tendem gives your AI direct access to vetted human experts for the work an agent alone can't nail: judgment-heavy research, competitive analysis, copywriting and editing, design review, data cleaning, and complex multi-step tasks. You (or your agent) submit a task in plain English — Tendem scopes the work, quotes a transparent price, and delivers verified results back into the chat as files, reports, or structured outputs. Agent plus expert raises the quality ceiling of what you can ship well beyond what either does alone.
Ideal for founders, creators, operators, and consultants who need reliable expert output without managing freelancers.
Get started → agent.tendem.ai.
This repo is the official distribution home for the Tendem MCP plugin — the part that lives in your AI client. Install it and your assistant arrives already knowing how to drive the full Tendem lifecycle: create → scope → approve → fetch, with clean polling and spend safety built in.
The MCP server itself is hosted at
https://mcp.tendem.ai/mcp— it is not in this repo. This repo contains the client-side plugins, skills, and rules that teach your AI client to use the hosted server well.
Start using Tendem
1. The web interface
Sign in at agent.tendem.ai to create your account, top up your balance, and watch tasks run end-to-end. The full output of every task — markdown plus downloadable files — is always available there, no matter which client you launched it from.
2. Install the plugin in your AI client
The hosted server URL is the same everywhere: https://mcp.tendem.ai/mcp
(streamable HTTP, OAuth on first use). Pick your client:
Claude Code
/plugin marketplace add Toloka/tendem-mcp
/plugin install tendem@tendem-mcp
OpenAI Codex / ChatGPT
codex plugin marketplace add Toloka/tendem-mcp
codex plugin add tendem@tendem-mcp
Complete the MCP server's OAuth login on first tool use.
GitHub Copilot CLI
copilot plugin marketplace add Toloka/tendem-mcp
copilot plugin install tendem@tendem-mcp
Gemini CLI
gemini extensions install https://github.com/Toloka/tendem-mcp
Then authenticate inside Gemini with /mcp auth tendem. The catalog entry is
gemini-extension.json at the repo root.
Kiro
Kiro Powers register through the IDE. Point Kiro at the
tendem-power/ steering bundle in this repo, then connect the
tendem MCP server when prompted.
Manual (any MCP-compatible client)
Add to your client's MCP config and sign in when prompted:
{
"mcpServers": {
"tendem": {
"type": "http",
"url": "https://mcp.tendem.ai/mcp"
}
}
}
Build agentic pipelines (API-key auth)
For headless, CI, or programmatic use — where the interactive OAuth flow isn't viable — authenticate with a Tendem API key instead: sign in at agent.tendem.ai/mcp and create one under the Agent builders tab.
Python / LangChain / LangGraph: skip the raw MCP wiring and use
langchain-tendem — four price-capped
tools that let an agent create a task, answer the service's questions, and
collect the verified result, with all polling in plain Python (no LLM, no
tokens).
For every other stack, a native "type": "http" remote server triggers the
interactive OAuth flow, so
to pass a static API key instead, bridge the connection through
mcp-remote — a local stdio process
that connects to the hosted URL and injects your Authorization: ApiKey header:
{
"mcpServers": {
"tendem": {
"command": "npx",
"args": [
"-y",
"mcp-remote",
"https://mcp.tendem.ai/mcp",
"--transport",
"http-only",
"--header",
"Authorization: ApiKey <your-tendem-api-key>"
]
}
}
}
Keep the token out of source control (inject it from an environment variable or
secret store). Your custom agent loop drives the same eleven tools the plugin
uses — create_task, get_task, get_contract, get_task_result,
list_tasks, approve_task, cancel_task, send_message, read_chat,
get_account, get_file_upload_url — to implement the create → scope →
approve → poll → fetch lifecycle yourself. The server ships a
tendem-quickstart prompt with a full walkthrough.
Spend safety:
approve_taskis what triggers a charge. In an automated pipeline, gate it behind your own approval logic and checkget_accountfirst — an insufficient balance returns a task-bound top-up URL, not an error to retry.
What's in this repo
| Path | What it is |
|---|---|
plugins/tendem/ | The plugin for Claude Code, Cursor, and GitHub Copilot CLI — skill, slash commands, background watcher agent, notification hook, and the MCP connector |
codex/tendem/ | The plugin for OpenAI Codex / ChatGPT — explicit $-skills and Codex-specific file-upload guidance |
tendem-power/ | The Kiro Power (steering + MCP config) |
gemini-extension.json | The Gemini CLI extension manifest (root install) |
.claude-plugin/marketplace.json | This repo's Claude Code marketplace |
.agents/plugins/marketplace.json | This repo's Codex marketplace |
server.json | MCP Registry manifest (remote server) |
llms.txt | LLM discovery index |
What the plugin teaches your assistant
Installing does more than wire up the connector — it ships steering so your AI handles Tendem correctly out of the box:
tendem-tasksskill — the end-to-end path (create → scope → approve → fetch), silent long-polling without busy-loops, scope negotiation, and live-verified file upload/download mechanics. Loads only when work actually involves Tendem./tendem-task,/tendem-status,/tendem-result— explicit entry points to submit, check, and fetch a task (in Codex these are$tendem-tasketc.).tendem-watcheragent (Claude / Copilot) — a background watcher that polls a running task at a slow pace and pings you the moment it needs you.- Notification hook — a desktop notification when a task transitions to needing you (quote ready, top-up needed, input needed, result ready).
For contributors
- AGENTS.md — guide for AI agents working in this repo
- CONTRIBUTING.md — how to contribute
- Per-client manifests: Claude Code, OpenAI Codex, Cursor, GitHub Copilot CLI, and Gemini CLI
Links
- Product: tendem.ai · App: agent.tendem.ai
- Overview: Connect your AI agent to human experts via MCP
- Legal: Privacy Policy · Terms of Use
- Support: Help center
Tendem MCP is part of the Model Context Protocol ecosystem.
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