ElizaOS MCP Plugin

Overview

The Eliza Plugin for MCP bridges ElizaOS agents with the Model Context Protocol, enabling them to tap into a rich ecosystem of external resources, prompts, and executable tools. By configuring multiple MCP servers—each potentially offering a different set of capabilities—developers can extend an agent’s knowledge base and action repertoire without modifying the core agent logic. This approach solves a common pain point in AI‑powered applications: the need to weave disparate data sources and utilities into a single, coherent workflow.

At its core, the plugin injects three context providers that expose MCP server information directly into the agent’s prompt. The provider lists available servers, along with their tools, resources, and prompts. This makes the server catalog discoverable by the language model during reasoning, allowing it to choose the most appropriate tool or resource dynamically. The plugin also handles the orchestration of tool calls, routing user requests to the selected MCP server and managing timeouts or error handling transparently.

Key capabilities include:

• Multi‑server support: Agents can simultaneously connect to several MCP servers, each possibly of type stdio (spawned as a local process) or sse (streaming over HTTP). This flexibility lets developers mix lightweight command‑line tools with heavy cloud services.
• Unified configuration: A single JSON block in the character definition declares all server connections, making it easy to add or remove servers without touching agent code.
• Automatic context injection: Once a server is configured, its tools and resources become part of the agent’s prompt context, enabling zero‑touch reasoning over external data.
• Robust tool selection flow: The plugin’s internal workflow uses the language model twice—first to select a tool and then to validate or retry if the selection is invalid—ensuring reliable execution.

Real‑world scenarios that benefit from this plugin include:

• Code generation and debugging: Connect to a GitHub‑based MCP server that provides repository context and code analysis tools, allowing agents to write or refactor code on the fly.
• Data‑driven decision making: Integrate with a data‑analytics MCP server that supplies up‑to‑date metrics, enabling agents to recommend business actions.
• Knowledge augmentation: Link to a knowledge‑base MCP server that hosts domain literature, giving agents access to specialized terminology and concepts.

By abstracting the complexities of tool discovery, selection, and execution behind a standardized protocol, the Eliza Plugin for MCP empowers developers to compose sophisticated AI workflows that seamlessly blend LLM reasoning with external capabilities.