
Tendem MCP server
io.github.Toloka由 GitHub 帳號 Toloka 發布v1.0.1更新於 Oct 24, 2026
Delegate tasks to vetted human experts - research, writing, analysis, and data work.
概覽
Tendem 將 AI 助理與經過審核的人類專家連結起來,可委派研究、寫作、分析與資料任務,取得報價、核准並取回結果。
- 可以做什麼
- 建立與管理專家任務:以自然語言提交任務、列出任務、收發聊天訊息、取消任務。檢視範圍與報價:取得任務合約並核准工作。收集結果:輪詢任務狀態,取回以檔案、報告或結構化資料形式交付的成果。帳戶與上傳:查詢帳戶餘額並取得檔案上傳位址。
- 適用情境
- 當助理需要完成難以獨力可靠完成的、仰賴判斷的人類工作時使用,例如競品研究、文案撰寫與編輯、設計審閱、資料清理或複雜的多步驟任務,並希望結果直接回到對話中。
- 執行需求
- 遠端 MCP 端點,使用 streamable HTTP,首次使用時透過 OAuth 登入;或使用 Tendem API 金鑰,以 Authorization 標頭傳入(例如透過本機 mcp-remote 橋接)。執行任務需要已儲值的 Tendem 帳戶。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 Tendem MCP server,將其新增到工作區。
- 連接 所需的 憑證。它們會被私密儲存,絕不會在公開頁面上展示。
- 為需要使用其工具的對話啟用該服務。
Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。
交給代理程式安裝
把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。
閱讀 https://sourceweft.com/mcp/io.github.Toloka%2Ftendem-mcp/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。其他 MCP 客戶端
把它新增到你客戶端的 mcpServers 設定中。 客戶端會在首次連接時完成 OAuth 登入。
{
"mcpServers": {
"tendem": {
"type": "http",
"url": "https://mcp.tendem.ai/mcp?utm_hash=b093faed05"
}
}
}README
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
OpenAI Codex / ChatGPT
Complete the MCP server's OAuth login on first tool use.
GitHub Copilot CLI
Gemini CLI
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:
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:
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
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.
來源:README.md,提交 683885a
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0版本歷史
1- v1.0.1最新Sep 16, 2026
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