Doist/todoist-mcp — A set of tools to connect to AI agents, to allow them to use Todoist on a user's behalf.

Description and use

**Brief Summary (2‑3 sentences)**
Doist’s **todoist‑mcp** is a TypeScript library that implements the Model Context Protocol (MCP) to let AI agents interact with a user’s Todoist account—creating, updating, and querying tasks on their behalf. By exposing Todoist’s functionality through a standard MCP interface, developers can rapidly prototype AI‑driven productivity assistants or integrate Todoist into larger AI‑centric workflows.

**Value**

• **Standardized AI‑to‑tool bridge** – MCP provides a common contract for AI agents, so the same integration code can be reused across different models or platforms.
• **Accelerates AI assistant development** – Instead of writing bespoke Todoist APIs for each assistant, developers plug the MCP server into their stack and immediately gain full task‑management capabilities.
• **Open‑source community backing** – With ~480 stars and active recent commits, the project already enjoys a modest community that can help troubleshoot and extend the integration.

**Practical Adoption Path**

1. **Proof‑of‑Concept** – Clone the repo, run the provided Docker/Node example, and verify that a simple prompt can add a task to a test Todoist account.
2. **Read‑me & MCP contract review** – Ensure the MCP schema matches your internal data model and adjust the mapping layer if needed.
3. **Secure credential handling** – Store the Todoist API token in a secret manager (e.g., Vault, AWS Secrets Manager) and configure the MCP server to load it at runtime.
4. **Iterative feature addition** – Start with core CRUD operations, then expand to task comments, labels, or project queries as the AI use case matures.
5. **Production hardening** – Add logging, rate‑limit handling, and automated tests around the MCP endpoints before rolling out to production.

**Production Readiness**

• **Maturity:** Medium. The library is functional and actively maintained (last update 2026‑05‑14) but has not been battle‑tested at large scale.
• **Suitability:** Ideal for prototypes, internal tools, or early‑stage AI assistants; production deployments should include additional safeguards (dependency audits, security scanning, monitoring).
• **Risks to address:** Verify the MIT‑style license compatibility, conduct a security review of the MCP server (exposed endpoints, token handling), and confirm that maintainers are responsive for critical bug fixes.

Overall, **todoist‑mcp** offers a low‑friction way to bring Todoist into AI‑driven workflows, with a clear path from a quick sandbox test to a hardened production service.

Problem

Doist/todoist-mcp helps connect AI assistants to real tools and data through a standard protocol.

Outcome

Medium: useful for prototypes or internal workflows, with dependency and maintenance checks before production.

Workflow

• connect AI agents to tools
• ship Model Context Protocol servers
• standardize integrations

Evidence

A set of tools to connect to AI agents, to allow them to use Todoist on a user's behalf. Includes MCP support.

Source