Allows sending GraphQL queries and mutations to any GraphQL API, with support for variables, headers, and token-efficient response summarization.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@lunge Send a GET request to https://jsonplaceholder.typicode.com/todos/1"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
An agent-native advanced API client - execute and test REST, GraphQL, WebSocket, SSE, and (later) gRPC requests from any MCP-capable AI agent. No GUI, no manual clicking, no heavyweight desktop app. Think advanced curl, native for agents.
It is a lightweight, token-efficient alternative to Postman/Bruno for the era of AI coding agents. The agent calls tools directly; there are no humans in the loop and no bloated feature surface to pay for.
Pain with Postman/Bruno | lunge approach |
Require human clicking in a GUI | Agent-native: everything is an MCP tool call |
Postman is heavy, enterprise features are paywalled | Small, open, single local binary + thin MCP layer |
Verbose responses blow up the LLM context window | Rust core summarizes/compresses output before it reaches the agent |
Collections are locked into proprietary formats | Plain YAML/JSON files, git-friendly |
Separate tools per protocol | One server for REST/GraphQL/WS/SSE/gRPC |
Related MCP server: Graft
Agent-native - designed for LLM tool calls, not human UIs.
Token-efficient - every response is filtered, truncated, and summarized. Full payloads are spilled to disk and referenced by handle so the context stays small.
Fast & portable - a Rust core (execution + protocols + summarization) exposed to a thin TypeScript MCP layer via napi-rs.
Both ad-hoc and reusable - agents can fire one-off requests or create, save, and re-run declarative collections stored as files.
Doc | Contents |
System design, the Rust/TS split, module layout, streaming strategy, FFI boundary | |
Full feature list by protocol + cross-cutting features (auth, vars, assertions, token optimizer) | |
The MCP tool surface: names, inputs, outputs, examples | |
The declarative YAML/JSON test/collection format | |
Phased delivery plan from scaffolding to gRPC and CI |
Stack: Rust core via napi-rs + TypeScript MCP layer (@modelcontextprotocol/sdk).
Distribution: local dev tool over stdio transport (used by Cursor/Windsurf/Claude Desktop).
Test definition: both ad-hoc agent calls and persisted declarative collections.
MVP protocols: REST, GraphQL, WebSocket, SSE. gRPC is a later phase.
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If you are the server author, to access and configure the admin panel.
Agent-native collaboration network: orchestrate a team of long-running agents from any MCP client.
OCR, transcription, file extraction, and image generation for AI agents via MCP.
AI Reasoning Cache & Consensus Layer with 11 MCP tools via Streamable HTTP.
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