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Servers/Code Execution/DataGrout
Code ExecutionOfficial
D

DataGrout

DataGrout - Discovery, governance, and orchestration layer for AI agents working across multiple MCP servers and integrations.

0 starsUpdated Aug 28, 2026

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Overview

Most MCP clients handle one job: send a request, get a response. Conduit is built for a slightly different problem — an agent that needs to prove who it is, keep working across long sessions without re-authenticating by hand, and stay inside a cost or policy budget while it does it. That's the gap this SDK fills. MCP client library with built-in mTLS, OAuth 2.1, and semantic tool discovery. Available for Python, TypeScript, Rust, Elixir, and Ruby. Swap a single import and an existing agent picks up certificate-based identity, cost visibility, and natural-language tool discovery — no other code changes required.

Installation

Installation instructions are not available yet.

Configuration

Configuration example is not available yet.

Capabilities

  • Provision a DataGrout server and mTLS identity automatically

    call `bootstrap_onramp` to register an agent, get OAuth credentials, and generate a signed certificate in one step.

  • Authenticate with mTLS, OAuth 2.1, or bearer tokens

    configure the client with certificate-based identity, auto-refreshing JWTs, or a simple token for testing.

  • Discover and invoke tools using natural language

    use the Intelligent Interface (`discover`/`perform`) to let an agent find and call tools by describing a goal instead of specifying exact tool names.

  • Track credit usage on every call

    inspect the cost receipt returned with each response to monitor spending against policy or budget limits.

  • Walk through multi-step goals interactively

    call `client.guide(goal=...)` to step through a guided workflow with the server.

  • Switch between Streamable HTTP, JSON-RPC, or WebSocket transports

    select `mcp`, `jsonrpc`, or `websocket` transport without changing authentication setup.

Tags

  • development

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