iagent-mesh-sdk (DevEx Hub)

This repository serves as the Data-Driven Developer Experience (DevEx) Hub and provides the iagent_mesh SDK core library, which includes universal contracts and an infrastructure wrapper for the iagent Mesh platform.

📖 Architectural Guide: Read Launch Domain Nodes, Not Scripts to understand why this framework is required for enterprise AI deployments.

Architecture & Features

This Hub leverages the Inception Pattern to dynamically scaffold new agent tools.

  • iagent_mesh Core Library: Contains MeshTool for routing, FastAPI execution, and Topaz Zero-Trust security.
  • Templates: Standardized data scientist environments (Pure Math, Instructor + Polars, BAML + Pandas).
  • Interactive Scaffolding: Use scripts/scaffold.sh to locally generate a new agent from a template.
  • MCP Server: The mcp_server/server.py exposes tools (scaffold_local_workspace, publish_local_to_mesh) for intelligent IDE-based agent creation.
  • Cloud Endpoints: app.py exposes REST APIs (scaffold_generator, mesh_publisher) for the central orchestrator to provision workspaces dynamically.

Environment Configuration

This SDK relies on centralized environment variables for all integrations to ensure no hardcoded enterprise strings are checked in. See the .env.example file in the root directory for a full list.

Required URLs:

  • GIT_PROVISION_API_URL: The platform provisioning API for repositories.
  • GIT_SERVER_HOST: The core Git server hostname.
  • ARTIFACTORY_BASE_URL: The enterprise artifact repository.

Optional URLs / tokens (only needed if MESH_REGISTER_ON_STARTUP=true):

  • DATAHUB_GMS_URL: The DataHub GMS endpoint the SDK pushes registrations to.
  • DATAHUB_TOKEN: Bearer token for the GMS emitter.

Required Tokens (Depending on deployment):

  • PLATFORM_GIT_TOKEN: Used by the cloud pod (app.py) for live git publishing.
  • MESH_DEV_TOKEN: Used by the local mcp_server to authenticate against provisioning APIs.

Installation & Testing

Data scientists can install the core SDK via:

uv pip install git+https://[your-repo-url]

To run the robust regression testing suite:

uv pip install -e ".[dev]"
python -m pytest

Project links

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  • Released:
Newer release available (0.5.0)

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Credits

Author: Chris Nogradi

GitHub Statistics

Data verified by PyPI on Sep 2, 2026
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License expression

MIT
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Requires

Python >=3.10

Provides Extra

dev

Tags

agents ai-mesh datahub fastapi knowledge-graph predicate-graph topaz

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