Overview

The Starknet MCP Server bridges the gap between AI assistants and the Starknet blockchain by exposing a lightweight, standards‑compliant Model Context Protocol (MCP) interface. Developers can now query blockchain state, retrieve block information, and eventually interact with smart contracts directly from an AI model’s context without writing custom RPC logic. This server solves the recurring pain point of integrating decentralized ledger data into conversational AI workflows, enabling richer, real‑time responses about on‑chain events, balances, and contract state.

At its core, the server implements a single tool——that accepts a block number and returns the corresponding Starknet block data. The tool is built on top of the official Starknet RPC endpoint, ensuring compatibility with any public or private node. By packaging this functionality behind the MCP protocol, Claude and other AI assistants can discover, invoke, and chain multiple such tools in a declarative manner. The value lies in decoupling blockchain access from application code: the AI orchestrates calls, handles error recovery, and presents results to users in natural language.

Key capabilities include:

• Standardized Discovery: The MCP server advertises its tools, prompts, and sampling methods via the protocol’s metadata. Clients can automatically list available actions without hard‑coding URLs or authentication details.
• Stateless Interaction: Each request is self‑contained, allowing the AI to perform a single block query and immediately receive structured JSON in return. This statelessness aligns with serverless or micro‑service architectures.
• Extensibility: The project’s TODO list outlines future tools for smart‑contract interaction, contract deployment, and event streaming. The modular TypeScript foundation makes it straightforward to add new endpoints while preserving the MCP contract.

Real‑world use cases include:

• Decentralized Finance (DeFi) Assistants: An AI can fetch the latest block to provide up‑to‑date price feeds or liquidity pool snapshots, then pass that data to other tools for yield calculations.
• Developer Debuggers: When troubleshooting a contract, the AI can query historical blocks to inspect state changes or revert to a specific snapshot.
• Educational Bots: Students learning Starknet can ask the assistant for block details and receive guided explanations, making blockchain concepts more approachable.

Integration into AI workflows is seamless. Once the MCP server is running, any MCP‑compatible client (e.g., Claude Desktop via Smithery) automatically registers the tool. The assistant can then include a call like:

and will receive a JSON payload that can be parsed and rendered in the conversation. This pattern scales: as more tools are added, the assistant can chain calls—fetch a block, query a contract’s state, then compute a result—all within a single conversational turn.

What sets this server apart is its focus on Starknet, a rapidly growing L2 that prioritizes low fees and high throughput. By providing an MCP gateway tailored to Starknet, developers can prototype AI‑driven dApps and analytics tools without wrestling with low‑level SDKs. The server’s minimal footprint, TypeScript foundation, and open‑source licensing further lower the barrier to adoption, making it an ideal starting point for any team looking to fuse conversational AI with blockchain data.