--- title: "AutoGPT vs mcpproxy-go" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/significant-gravitas-autogpt-vs-smart-mcp-proxy-mcpproxy-go" tools: ["significant-gravitas-autogpt", "smart-mcp-proxy-mcpproxy-go"] --- # AutoGPT vs mcpproxy-go *GraphCanon updated Jul 12, 2026* ## Verdict Pick AutoGPT when autoGPT is primarily Python; mcpproxy-go is Go; pick mcpproxy-go when mcpproxy-go is primarily Go; AutoGPT is Python. [AutoGPT](https://agpt.co) reports 185k GitHub stars, 46k forks, and 494 open issues, last pushed Jul 11, 2026. [mcpproxy-go](https://mcpproxy.app) has 285 stars, 36 forks, and 14 open issues, last pushed Jul 11, 2026. Figures are from public GitHub metadata via [AutoGPT's repository](https://github.com/Significant-Gravitas/AutoGPT) and [mcpproxy-go's repository](https://github.com/smart-mcp-proxy/mcpproxy-go). | | [AutoGPT](/tools/significant-gravitas-autogpt.md) | [mcpproxy-go](/tools/smart-mcp-proxy-mcpproxy-go.md) | | --- | --- | --- | | Tagline | AutoGPT is the vision of accessible AI for everyone, to use and to build on. | Supercharge AI Agents, Safely | | Stars | 185,464 | 285 | | Forks | 46,111 | 36 | | Open issues | 494 | 14 | | Language | Python | Go | | Adopt for | AutoGPT is a Python-based tool for creating accessible autonomous AI agents that can leverage various LLM APIs including OpenAI's GPT and Anthropic's Claude. | - | | Persona | - | - | | Runtime | - | - | | License | Other | MIT | | Categories | AI Agents, LLM Frameworks | AI Agents, Developer Tools, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [AutoGPT](/tools/significant-gravitas-autogpt.md) | [mcpproxy-go](/tools/smart-mcp-proxy-mcpproxy-go.md) | | --- | --- | --- | | Open issues (now) | 494 | 14 | | Security scan | No lockfile | No criticals | | Full report | [trust report](/tools/significant-gravitas-autogpt/trust.md) | [trust report](/tools/smart-mcp-proxy-mcpproxy-go/trust.md) | ## Decision facts: AutoGPT - **Adopt for:** AutoGPT is a Python-based tool for creating accessible autonomous AI agents that can leverage various LLM APIs including OpenAI's GPT and Anthropic's Claude. ## Choose when ### Choose AutoGPT if… - AutoGPT is primarily Python; mcpproxy-go is Go. - License: AutoGPT is Other, mcpproxy-go is MIT. - Tags unique to AutoGPT: agentic-ai, agents, artificial-intelligence, autonomous-agents. - When you need to rapidly prototype or deploy an autonomous agent using existing language models without deep AI expertise. ### Choose mcpproxy-go if… - mcpproxy-go is primarily Go; AutoGPT is Python. - License: mcpproxy-go is MIT, AutoGPT is Other. - Tags unique to mcpproxy-go: ai-agents, audit-logging, bm25, cli. - Also covers Developer Tools. - mcpproxy-go ships Docker support for self-hosted deployment. ## When NOT to use AutoGPT - Avoid if you require absolute control over the underlying AI infrastructure and APIs used by your autonomous agents, as AutoGPT imposes its own framework. - If your project demands proprietary or specialized models that aren't supported by AutoGPT's API ecosystem (e.g., custom TensorFlow or PyTorch models), consider other tools. ## When NOT to use mcpproxy-go - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - Developer Tools: A gateway is overkill when you're pinned to a single provider and model. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## Common questions ### What is the difference between AutoGPT and mcpproxy-go? AutoGPT: AutoGPT is the vision of accessible AI for everyone, to use and to build on.. mcpproxy-go: Supercharge AI Agents, Safely. See the comparison table for live GitHub stats and shared categories. ### When should I choose AutoGPT over mcpproxy-go? Choose AutoGPT over mcpproxy-go when AutoGPT is primarily Python; mcpproxy-go is Go; License: AutoGPT is Other, mcpproxy-go is MIT; Tags unique to AutoGPT: agentic-ai, agents, artificial-intelligence, autonomous-agents; When you need to rapidly prototype or deploy an autonomous agent using existing language models without deep AI expertise. ### When should I choose mcpproxy-go over AutoGPT? Choose mcpproxy-go over AutoGPT when mcpproxy-go is primarily Go; AutoGPT is Python; License: mcpproxy-go is MIT, AutoGPT is Other; Tags unique to mcpproxy-go: ai-agents, audit-logging, bm25, cli; Also covers Developer Tools; mcpproxy-go ships Docker support for self-hosted deployment. ### When should I avoid AutoGPT? Avoid if you require absolute control over the underlying AI infrastructure and APIs used by your autonomous agents, as AutoGPT imposes its own framework. If your project demands proprietary or specialized models that aren't supported by AutoGPT's API ecosystem (e.g., custom TensorFlow or PyTorch models), consider other tools. ### When should I avoid mcpproxy-go? AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Developer Tools: A gateway is overkill when you're pinned to a single provider and model. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### Is AutoGPT or mcpproxy-go more popular on GitHub? AutoGPT has more GitHub stars (185,464 vs 285). Stars measure visibility, not whether either tool fits your constraints. ### Are AutoGPT and mcpproxy-go open source? Yes - both are open-source projects on GitHub (AutoGPT: Other, mcpproxy-go: MIT). ### Where can I find alternatives to AutoGPT or mcpproxy-go? GraphCanon lists graph-backed alternatives at [AutoGPT alternatives](/tools/significant-gravitas-autogpt/alternatives) and [mcpproxy-go alternatives](/tools/smart-mcp-proxy-mcpproxy-go/alternatives) ([AutoGPT markdown twin](/tools/significant-gravitas-autogpt/alternatives.md), [mcpproxy-go markdown twin](/tools/smart-mcp-proxy-mcpproxy-go/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/significant-gravitas-autogpt-vs-smart-mcp-proxy-mcpproxy-go.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, AutoGPT or mcpproxy-go? AutoGPT: Very active. mcpproxy-go: Very active. 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 AutoGPT and mcpproxy-go? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [AutoGPT trust report](/tools/significant-gravitas-autogpt/trust); [mcpproxy-go trust report](/tools/smart-mcp-proxy-mcpproxy-go/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=significant-gravitas-autogpt`](/api/graphcanon/graph?tool=significant-gravitas-autogpt) - 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/_