--- title: "mcp-context-forge vs openpi" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ibm-mcp-context-forge-vs-physical-intelligence-openpi" tools: ["ibm-mcp-context-forge", "physical-intelligence-openpi"] --- # mcp-context-forge vs openpi *GraphCanon updated Aug 26, 2026* ## Verdict Pick mcp-context-forge if mcp-context-forge is an AI gateway and registry for MCP, A2A, REST/gRPC APIs. It offers centralized discovery, guardrails, management, and optimization for agent and tool calling in Python; pick openpi if openpi is a specialized tool for model training, inference & serving that leverages advanced GPU capabilities and has specific requirements for memory and hardware configurations. [mcp-context-forge](https://ibm.github.io/mcp-context-forge/) reports 4.4k GitHub stars, 837 forks, and 1.2k open issues, last pushed Aug 25, 2026. [openpi](https://github.com/Physical-Intelligence/openpi) has 13k stars, 2.3k forks, and 316 open issues, last pushed Jun 16, 2026. Figures are from public GitHub metadata via [mcp-context-forge's repository](https://github.com/IBM/mcp-context-forge) and [openpi's repository](https://github.com/Physical-Intelligence/openpi). | | [mcp-context-forge](/tools/ibm-mcp-context-forge.md) | [openpi](/tools/physical-intelligence-openpi.md) | | --- | --- | --- | | Tagline | AI Gateway and registry for MCP, A2A, REST/gRPC APIs | Repository for running AI models with GPU requirements specified. | | Stars | 4,368 | 13,098 | | Forks | 837 | 2,276 | | Open issues | 1,187 | 316 | | Language | Python | Python | | Adopt for | mcp-context-forge is an AI gateway and registry for MCP, A2A, REST/gRPC APIs. It offers centralized discovery, guardrails, management, and optimization for agent and tool calling in Python. | openpi is a specialized tool for model training, inference & serving that leverages advanced GPU capabilities and has specific requirements for memory and hardware configurations. | | Persona | - | - | | Runtime | - | - | | License | Available under the Apache License 2.0 | Apache-2.0 | | Categories | Developer Tools, Evaluation & Observability, Inference & Serving | Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [mcp-context-forge](/tools/ibm-mcp-context-forge.md) | [openpi](/tools/physical-intelligence-openpi.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Steady (60%) | | Days since push | 0d | 46d | | Open issues (now) | 1.2k | 316 | | Stars delta | +225 (30d) | Unknown | | Open issues delta | +29 (30d) | Unknown | | Full report | [trust report](/tools/ibm-mcp-context-forge/trust.md) | [trust report](/tools/physical-intelligence-openpi/trust.md) | ## Decision facts: mcp-context-forge - **Pricing:** freemium - Open-source, free to use for both personal and commercial projects. - **Requirements:** Requires Docker; Supports running with Docker for ease of deployment. - **Adopt for:** mcp-context-forge is an AI gateway and registry for MCP, A2A, REST/gRPC APIs. It offers centralized discovery, guardrails, management, and optimization for agent and tool calling in Python. - **License detail:** Available under the Apache License 2.0 ## Decision facts: openpi - **Adopt for:** openpi is a specialized tool for model training, inference & serving that leverages advanced GPU capabilities and has specific requirements for memory and hardware configurations. ## Choose when ### Choose mcp-context-forge if… - Pricing: Open-source, free to use for both personal and commercial projects.. - Requirements: Requires Docker; Supports running with Docker for ease of deployment.. - Tags unique to mcp-context-forge: agents, ai-gateway, authentication-middleware, devops. - Also covers Developer Tools, Evaluation & Observability. - mcp-context-forge ships Docker support for self-hosted deployment. - When you need to integrate multiple APIs using a unified endpoint with support for MCP, Agent-to-Agent communication, or REST/gRPC services. ### Choose openpi if… - Tags unique to openpi: fine-tuning, lora, model parallelism, nvidia gpu. - Also covers Model Training. - When you have an NVIDIA GPU with at least 8 GB of VRAM for inference or at least 22.5 GB to fine-tune models using LoRA (Low-Rank Adaptation) on a single GPU. ## When NOT to use mcp-context-forge - When only REST API support is required, without additional functionality such as MCP or A2A services. - For applications that do not benefit from centralized discovery and management features for AI agents, preferring more decentralized approaches to development. - If your project is built in a language other than Python and integration with third-party plugins is unnecessary. ## When NOT to use openpi - When your project is not compatible with Ubuntu 22.04 or if you do not have access to a supported GPU configuration. - If you need to support multi-node training, as this capability has yet to be implemented in the current version of openpi. ## Common questions ### What is the difference between mcp-context-forge and openpi? mcp-context-forge: AI Gateway and registry for MCP, A2A, REST/gRPC APIs. openpi: Repository for running AI models with GPU requirements specified.. See the comparison table for live GitHub stats and shared categories. ### When should I choose mcp-context-forge over openpi? Choose mcp-context-forge over openpi when Pricing: Open-source, free to use for both personal and commercial projects.; Requirements: Requires Docker; Supports running with Docker for ease of deployment.; Tags unique to mcp-context-forge: agents, ai-gateway, authentication-middleware, devops; Also covers Developer Tools, Evaluation & Observability; mcp-context-forge ships Docker support for self-hosted deployment; When you need to integrate multiple APIs using a unified endpoint with support for MCP, Agent-to-Agent communication, or REST/gRPC services. ### When should I choose openpi over mcp-context-forge? Choose openpi over mcp-context-forge when Tags unique to openpi: fine-tuning, lora, model parallelism, nvidia gpu; Also covers Model Training; When you have an NVIDIA GPU with at least 8 GB of VRAM for inference or at least 22.5 GB to fine-tune models using LoRA (Low-Rank Adaptation) on a single GPU. ### When should I avoid mcp-context-forge? When only REST API support is required, without additional functionality such as MCP or A2A services. For applications that do not benefit from centralized discovery and management features for AI agents, preferring more decentralized approaches to development. If your project is built in a language other than Python and integration with third-party plugins is unnecessary. ### When should I avoid openpi? When your project is not compatible with Ubuntu 22.04 or if you do not have access to a supported GPU configuration. If you need to support multi-node training, as this capability has yet to be implemented in the current version of openpi. ### Is mcp-context-forge or openpi more popular on GitHub? openpi has more GitHub stars (13,098 vs 4,368). Stars measure visibility, not whether either tool fits your constraints. ### Are mcp-context-forge and openpi open source? Yes - both are open-source projects on GitHub (mcp-context-forge: Apache-2.0, openpi: Apache-2.0). ### Where can I find alternatives to mcp-context-forge or openpi? GraphCanon lists graph-backed alternatives at [mcp-context-forge alternatives](/tools/ibm-mcp-context-forge/alternatives) and [openpi alternatives](/tools/physical-intelligence-openpi/alternatives) ([mcp-context-forge markdown twin](/tools/ibm-mcp-context-forge/alternatives.md), [openpi markdown twin](/tools/physical-intelligence-openpi/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/ibm-mcp-context-forge-vs-physical-intelligence-openpi.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, mcp-context-forge or openpi? mcp-context-forge: Very active. openpi: Steady. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for mcp-context-forge and openpi? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [mcp-context-forge trust report](/tools/ibm-mcp-context-forge/trust); [openpi trust report](/tools/physical-intelligence-openpi/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=ibm-mcp-context-forge`](/api/graphcanon/graph?tool=ibm-mcp-context-forge) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_