MPC Tally API Server

Overview

The MPC Tally API Server is a purpose‑built Model Context Protocol (MCP) endpoint that bridges AI assistants with the Tally platform, a leading data hub for decentralized autonomous organizations (DAOs). By exposing a GraphQL‑backed MCP interface, the server lets agents query up to thousands of DAO records in a single request while keeping the payload manageable through built‑in pagination. This eliminates the need for custom HTTP wrappers or manual API key handling, allowing developers to focus on building higher‑level business logic.

At its core, the server solves a common pain point: accessing up‑to‑date DAO metadata and governance information in an AI‑friendly way. Tally’s REST API requires authentication, rate limiting, and manual pagination logic—all of which are abstracted away by the MCP server. An AI agent can simply call with optional filters and receive a clean, structured response that includes DAO identifiers, names, social links, governance models, and current proposal counts. The server also supports sorting by popularity or exploration status, enabling agents to surface the most active communities or those newly discovered.

Key capabilities are intentionally lightweight yet powerful:

• Pagination – The parameter lets agents fetch large datasets incrementally without overloading memory or the network.
• Sorting – Four sortable fields (, , , ) give agents control over how results are ordered, supporting use cases from trend analysis to targeted outreach.
• TypeScript & GraphQL – Strong typing and schema introspection mean agents can auto‑generate prompts or validate responses against a known contract, reducing runtime errors.
• Full test coverage – Built with Bun’s test runner, the server guarantees reliability and eases maintenance for teams that value robust CI pipelines.

Real‑world scenarios where this MCP shines include:

• DAO discovery bots that surface emerging communities for investors or collaborators.
• Governance analytics tools that aggregate proposal statistics across many DAOs to feed into portfolio dashboards.
• Community management assistants that pull social links and metadata to auto‑populate newsletters or internal reports.

Integration into an AI workflow is straightforward: a Claude (or other MCP‑compatible) assistant can invoke as part of a conversation, receive the structured result, and then use that data to generate summaries, answer user queries, or trigger downstream actions. Because the server handles authentication and pagination transparently, developers can embed it into larger pipelines—such as fetching DAO data, running sentiment analysis on proposals, and storing insights in a knowledge graph—all without writing custom API glue code.

What sets the MPC Tally API Server apart is its minimalistic yet complete approach: a single, well‑documented MCP endpoint that encapsulates the complexity of Tally’s API while offering developers a clean, type‑safe interface. This makes it an attractive choice for teams building AI assistants that need reliable DAO data, whether for research, product features, or community engagement.