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truefoundry/trueforge?utm_source=trendshift.io: Trending on GitHub

August 20, 2026
5 min
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By ZadeNor AI Team
truefoundry/trueforge?utm_source=trendshift.io: Trending on GitHub

truefoundry/trueforge?utm_source=trendshift.io: Trending on GitHub

The open-source agent harness - the runtime layer that turns an LLM into a working agent

TrueForge

TrueForge runs the agent execution loop for you - model calls, MCP tools, skills, sandboxing, approvals, context management, and session state - and exposes it three ways: a chat UI, an HTTP API with a TypeScript SDK, and an embeddable UI SDK.

Why TrueForge?

Building an agent is easy. Running one well is not - you need streaming, session persistence, tool servers, sandboxing, approvals, and a UI. TrueForge gives you that out of the box:

Initial setup from catalogs - configure models, MCP servers, skills, and a sandbox once; agents pick from what you connected. Presets come from shipped YAML catalogs you can customize.

Any model provider - OpenAI, Anthropic, Google Gemini, and other catalog providers, or any OpenAI-compatible endpoint.

MCP tools - remote MCP servers with header auth or OAuth, including in-chat authorization.

Skills - git-backed SKILL.md instruction packs, loaded on demand in the sandbox.

Sandbox as a tool - isolated code/file execution (Daytona today; more providers planned), provisioned only when needed. Secrets stay in the harness.

Human checkpoints - tool approval, ask-user-questions, and Generative UI in chat.

Context engineering - subagents, deferred tool loading, Code Mode, large-result offloading, and compaction.

Chat UI + SDK - use the bundled UI, automate with @truefoundry/trueforge-sdk, or embed @truefoundry/trueforge-ui.

It scales down and up: local mode (one process, SQLite) or hosted mode (Postgres + Redis, Docker Compose or Helm).

Getting started

Run TrueForge (local, Docker Compose, or Kubernetes), connect a model and tools, and build your first reusable agent in the Quickstart.

To work on TrueForge from this repository, see CONTRIBUTING.md.

Architecture

Mode Best for Storage Extra infra How to run

Local Personal use, trying it out SQLite None npx @truefoundry/trueforge

Hosted Teams, multi-replica Postgres Postgres + Redis Docker Compose or Helm

Local mode is for your machine only. It is a convenient way to try TrueForge — not a production or internet-facing setup. There is no login by default, and data lives in a local SQLite file. Please keep it on localhost. We cannot take responsibility for data loss or unauthorized access if local mode is used beyond that. For a shared or production deployment, use hosted mode.

Documentation

Section What you'll find

Introduction What an agent harness is and how TrueForge fits together

Quickstart Run local or hosted, build your first agent

Initial Setup Models, MCP, skills, sandbox - catalogs and overrides

Create an Agent Select resources; tool approval, questions, Generative UI

Harness Capabilities Sandbox-as-tool, subagents, deferred tools, Code Mode, compaction

Setup Login Optional OIDC for shared deployments

Benchmarking Cost/accuracy vs Claude Managed Agents and deepagents

SDK TypeScript client: sessions, turns, events

Chat UI Bundled UI and embedding @truefoundry/trueforge-ui

API Reference OpenAPI paths and schemas

Benchmarks

We compare TrueForge against Claude Managed Agents and deepagents on the same tasks, tools, and model - same accuracy, lower cost. Reproduce it from benchmark/. Write-up: Benchmarking.

Contributing

We love contributions - bug reports, features, and docs fixes. See CONTRIBUTING.md and our Code of Conduct. Fork PRs should change source only; maintainers regenerate the SDK after merge.

To report a security vulnerability, follow SECURITY.md instead of opening a public issue.

Talk to us

Community Discord

Founder emails: abhishek@truefoundry.com / anuraag@truefoundry.com

License

TrueForge is released under the MIT License.


Source: https://github.com/truefoundry/trueforge?utm_source=trendshift.io

About the Author

ZadeNor AI Team is a leading expert in AI, contributing to cutting-edge research and development in the field.