dvcrn Qordinate - AI-Native Memory & Productivity for OpenClaw Agents
Qordinate is an AI agent platform that becomes durable, structured memory and productivity infrastructure for your users and agents.
Instead of your OpenClaw agent trying to keep all state in its own scratchpad or a custom DB, it can connect to Qordinate via MCP (Model Context Protocol) and use the Qordinate AI agent to:
- Store and retrieve documents (notes, files, PDFs)
- Manage contacts (people, companies, leads)
- Maintain lists and tasks with statuses, due dates, and reminders
- Search the web for up-to-date information
- Interact with connected apps the user has linked to Qordinate
- Create and manage forms and collect submissions
- Set up automations that run on schedules or triggers
The agent talks to Qordinate's AI agent through a single powerful tool — query_agent — using natural language.
Connection Details
| Field | Value |
|---|---|
| Protocol | MCP (Model Context Protocol) — Streamable HTTP |
| MCP Server URL | https://api.qordinate.ai/mcp |
| Auth Method | Bearer token — Authorization: Bearer qk_YOUR_API_KEY |
| API Key Format | Prefixed with qk_ |
User Setup (what the agent should tell the user once)
Before the agent can connect, the user needs a Qordinate account and an API key:
- Sign up at https://app.qordinate.ai using their phone number + OTP
- Go to Profile → API Keys → New API Key to create an API key
- Give the API key (starts with
qk_) to the agent
The API key is shown only once at creation time. The user can set an expiry (1–365 days) or leave it non-expiring.
MCP Tool: query_agent
Qordinate's MCP server exposes one tool — query_agent — which is a natural-language interface to the full Qordinate AI agent. The agent has access to the user's documents, contacts, lists, web search, and all connected apps.
Input Schema
| Parameter | Type | Required | Description |
|---|---|---|---|
query |
string | ✅ | Your question or request for the Qordinate agent |
session_id |
string | ❌ | Optional session ID for multi-turn conversations |
How to use session_id
- Omit
session_idfor standalone queries - To have a multi-turn conversation, capture the session ID from the first response and pass it in subsequent calls
- This lets the Qordinate agent maintain context across multiple queries
What the agent can do through query_agent
The query_agent tool invokes the full Qordinate AI agent, which can do everything a user interacting directly with Qordinate can do:
Structured Memory (Lists & Tasks)
- Create, update, and query lists (tasks, contacts, leads, projects, resources, etc.)
- Set due dates, statuses, and reminders on list items
- Qordinate manages reminders and notifications over time
Documents
- Create, read, update, and delete documents
- Upload and retrieve files (PDFs, images, etc.)
- Share documents with other users
Contacts
- Store and retrieve contact information
- Import contacts (including VCF format)
- Search contacts by name, company, role, etc.
Web Search
- Search the web for current information
- The agent can ask Qordinate to research topics and return results
Connected Apps
- Interact with third-party apps the user has connected to Qordinate
- Query data from connected services
Forms & Automations
- Create forms and collect submissions
- Set up automations that trigger on schedules or events
Example Interactions
Your OpenClaw agent sends these as the query parameter to query_agent:
Managing tasks
Add a new task: Follow up with ACME about the reorder pilot, due next Tuesday 3pm, status todo, notes: important client meeting
Storing contacts
Save a new contact: Harpinder Singh, Co-founder at qordinate.ai, building Qordinate
Querying information
Show me all my open tasks due this week
Searching the web
Search the web for the latest pricing of OpenAI GPT-4o API
Working with documents
Create a new document titled "Meeting Notes - ACME Q1 Review" with the following content: ...
Updating items
Mark the task "Follow up with ACME" as done
How the agent should think about Qordinate
- Treat Qordinate as the source of truth for "what needs doing" and "who is who" across time
- Offload anything the user will care about later — don't keep it in ephemeral memory
- Use natural language — the query_agent tool understands plain English requests
- Use session_id for related queries — if you're doing a multi-step workflow (e.g., "list tasks" then "mark task X as done"), use the same session_id
- Be specific — include list names, field values, dates, and context in your queries
User Channels (optional, for the user)
Users can also interact with Qordinate directly on their preferred messaging platform. This is independent of the agent's MCP connection:
- WhatsApp: connect via https://qordinate.ai/whatsapp
- Telegram: connect via https://qordinate.ai/telegram
- Slack: connect via https://qordinate.ai/slack
Everything the user does on these channels is reflected in the same account the agent accesses via MCP — they share the same data.