Tendem MCP
Tendem MCP lets you delegate tasks to vetted human experts directly from your AI assistant, managing the full task lifecycle from creation to result retrieval.
Create tasks — Submit a task in plain English to human experts across specializations: data scraping, software development, design, copywriting, and general research/data work.
List tasks — Retrieve a paginated list of all your tasks with their statuses and details.
Check task status — Poll a specific task's current status (DRAFT → AWAITING_APPROVAL → PROCESSING → COMPLETED/CANCELLED/FAILED) and view pricing details once scoped.
Approve tasks — Review the quoted price and approve a task to trigger a charge and start human expert work.
Cancel tasks — Cancel a task at any stage (note: costs are not refunded after approval).
Fetch final results — Retrieve the final result text/report from a completed task.
Browse all result drafts — Access a paginated history of all intermediate and final results for a task, from latest to oldest.
Download file artifacts — Download files (images, documents) produced by experts and save them locally, using artifact references found in task results.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Tendem MCP delegate the task of researching competitors in the AI automation space"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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-mcpOpenAI Codex / ChatGPT
codex plugin marketplace add Toloka/tendem-mcp
codex plugin add tendem@tendem-mcpComplete 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-mcpGemini CLI
gemini extensions install https://github.com/Toloka/tendem-mcpThen 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"
}
}
}Related MCP server: human-delegation
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 |
The plugin for Claude Code, Cursor, and GitHub Copilot CLI — skill, slash commands, background watcher agent, notification hook, and the MCP connector | |
The plugin for OpenAI Codex / ChatGPT — explicit | |
The Kiro Power (steering + MCP config) | |
The Gemini CLI extension manifest (root install) | |
This repo's Claude Code marketplace | |
This repo's Codex marketplace | |
MCP Registry manifest (remote server) | |
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
Legal: Privacy Policy · Terms of Use
Support: Help center
Tendem MCP is part of the Model Context Protocol ecosystem.
Available Tools
8 toolsapprove_taskAInspect
Approve a Tendem task and its price. A human expert will begin working (may take hours).
Call after reviewing the price in AWAITING_APPROVAL status. A human expert will then work on the task until it reaches COMPLETED status (may take hours).
Args: task_id: The Tendem task ID (UUID) to approve.
Returns: Confirmation message.
Inputs: task_id (required). Returns: result
cancel_taskAInspect
Cancel a Tendem task. Costs are not refunded after approval.
Can be called at any time. Note: costs are not refunded if cancelled after approval.
Args: task_id: The Tendem task ID (UUID) to cancel.
Returns: Confirmation message.
Inputs: task_id (required). Returns: result
create_taskAInspect
Create a new Tendem task for a human expert.
Poll get_task until AWAITING_APPROVAL to see the price.
After creation, poll with get_task until status is AWAITING_APPROVAL to see the price (may take up to 10 minutes).
When creating a task consider available human expert specializations: 1. data_scraping
Task types: High-volume data extraction, scraping, cleansing and enrichment (web, social media, or document sets).
Threshold: MUST be used when manual effort would exceed ~4 hours OR when tools like Selenium/BS4/Apify are required. 2. software_development
Task types: Debugging/refactoring existing code. Writing automation scripts. Building full-stack apps (Python, Node, TS). Building/adding features to WordPress, Woocommerce, Shopify based websites and stores. 3. design
Task types: Logos, Branding, Presentations (decks), Print Materials (flyers/brochures/billboards), and Packaging. 4. copywriting
Definition: Writing where style, tone, and usage of language is important.
Task types: SEO Writing, Newsletters, Press Releases, Case Studies, Ad Copy, Landing Page texts, Social Media posts, UX Writing, Email campaigns, Proofreading, editing, refining and humanizing ai text. 5. general
Definition: Expert level knowledge not required, good at attention to detail, using software and ai tools.
Task types: Manual data collection, enrichment, cleaning and analysis (incl. lead generation, contact list building), market research, formatting documents, converting files.
Avoid tasks that: Required Regulated Expertise: Medical diagnosis, legal advice, PhD-level research, or real-money investment advice. Required access to private/internal systems without providing credentials e.g., "Check my email"
Args: text: The task description/prompt to execute.
Returns: The created task.
Inputs: text (required). Returns: Unified task representation for MCP API. Used for task creation, status queries…
download_artifactAInspect
Download a file artifact (image, document) from Tendem task results and save locally.
Artifact references appear in canvas content as:
aba://<artifact_id>Args: task_id: The Tendem task ID (UUID). artifact_id: The artifact ID (UUID) from the agents-reference block. path: The file path where the artifact should be saved.
Returns: Confirmation message with the saved file path and size.
Inputs: task_id (required), artifact_id (required), path (required). Returns: result
get_all_task_resultsBInspect
Get all Tendem task results including intermediate drafts, from latest to oldest.
Args: task_id: The Tendem task ID (UUID) to get results for. page_number: Page number (0-indexed). page_size: Number of results per page (1-100).
Returns: Paginated Tendem task results with canvas content.
Inputs: task_id (required), page_number (required), page_size (required). Returns: Paginated results for get_all_task_results tool.
get_taskAInspect
Get Tendem task status and details. Use to poll after create_task or approve_task.
Use to poll task status. After create_task, wait for AWAITING_APPROVAL to see price. After approve_task, a human expert works on the task until COMPLETED (may take hours).
Args: task_id: The Tendem task ID (UUID) to get.
Returns: The Tendem task including status and approval info if awaiting approval.
Inputs: task_id (required). Returns: Unified task representation for MCP API. Used for task creation, status queries…
get_task_resultAInspect
Get the final result text from a completed Tendem task.
Args: task_id: The Tendem task ID (UUID).
Returns: The content of the latest canvas, or an error if task is not completed.
Inputs: task_id (required). Returns: result
list_tasksAInspect
List all Tendem tasks with their statuses.
Args: page_number: Page number (0-indexed). page_size: Number of results per page (1-100).
Returns: Paginated list of Tendem tasks.
Inputs: page_number (required), page_size (required). Returns: Paginated list of tasks.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 8 tools
Each tool targets a distinct action on tasks or artifacts: approve, cancel, create, download, get status, get final result, get all results, and list. No overlap in functionality.
All tool names follow a consistent verb_noun pattern (e.g., approve_task, download_artifact) using lowercase and underscores, making it easy to predict tool names.
With 8 tools, the set covers the full lifecycle of task management without being bloated or sparse. Each tool has a clear purpose.
The tools cover creation, approval, cancellation, status polling, result retrieval (single and all), artifact download, and listing. The only missing operation is updating a task, but that is not critical for the typical workflow.
Maintenance
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