--- title: "forge vs LeanCopilot" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/antoinezambelli-forge-vs-lean-dojo-leancopilot" tools: ["antoinezambelli-forge", "lean-dojo-leancopilot"] --- # forge vs LeanCopilot *GraphCanon updated Aug 25, 2026* ## Verdict Pick forge if developers working on self-hosted LLM tooling who need flexibility in backend setup and seamless integration of function calling in multi-step workflows might benefit from Forge; pick LeanCopilot if a system that leverages large language models for theorem proving in the Lean environment. [forge](https://github.com/antoinezambelli/forge) reports 2.2k GitHub stars, 173 forks, and 4 open issues, last pushed Aug 13, 2026. [LeanCopilot](https://leandojo.org/leancopilot.html) has 1.3k stars, 127 forks, and 0 open issues, last pushed Aug 22, 2026. Figures are from public GitHub metadata via [forge's repository](https://github.com/antoinezambelli/forge) and [LeanCopilot's repository](https://github.com/lean-dojo/LeanCopilot). | | [forge](/tools/antoinezambelli-forge.md) | [LeanCopilot](/tools/lean-dojo-leancopilot.md) | | --- | --- | --- | | Tagline | A Python framework for self-hosted LLM tool-calling and multi-step agentic workflows | LLMs as Copilots for Theorem Proving in Lean | | Stars | 2,217 | 1,314 | | Forks | 173 | 127 | | Open issues | 4 | 0 | | Language | Python | C++ | | Adopt for | Developers working on self-hosted LLM tooling who need flexibility in backend setup and seamless integration of function calling in multi-step workflows might benefit from Forge. | A system that leverages large language models for theorem proving in the Lean environment. | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | AI Agents, LLM Frameworks | AI Agents, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [forge](/tools/antoinezambelli-forge.md) | [LeanCopilot](/tools/lean-dojo-leancopilot.md) | | --- | --- | --- | | Days since push | 0d | 2d | | Open issues (now) | 4 | 0 | | Stars delta | Unknown | +11 (30d) | | Open issues delta | Unknown | -5 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/antoinezambelli-forge/trust.md) | [trust report](/tools/lean-dojo-leancopilot/trust.md) | ## Decision facts: forge - **Requirements:** Min 4 GB RAM; Requires Docker; Requires Python 3.12+ and a running LLM backend.; Can be set up with local backends (e.g., llama.cpp) or Anthropic via its API, requiring an API key for the latter case. - **Adopt for:** Developers working on self-hosted LLM tooling who need flexibility in backend setup and seamless integration of function calling in multi-step workflows might benefit from Forge. ## Decision facts: LeanCopilot - **Adopt for:** A system that leverages large language models for theorem proving in the Lean environment. ## Choose when ### Choose forge if… - forge is primarily Python; LeanCopilot is C++. - Requirements: Min 4 GB RAM; Requires Docker; Requires Python 3.12+ and a running LLM backend.; Can be set up with local backends (e.g., llama.cpp) or Anthropic via its API, requiring an API key for the latter case.. - Tags unique to forge: agentic-ai, function-calling, multi-step-workflows, python-framework. - - You require an agnostic backend setup, such as local LLM backends like llama.cpp or cloud-based services with Anthropic. ### Choose LeanCopilot if… - LeanCopilot is primarily C++; forge is Python. - Tags unique to LeanCopilot: formal-mathematics, lean, lean4, llm. - Need support with formal proof development in Lean or Lean4 specifically ## When NOT to use forge - - If your application does not require flexibility in backend selection, and you prefer a single cloud provider like Anthropic without local setup. - - For scenarios where simplicity of setup outweighs the need for customization in function calling and workflow management. - - When working within environments strictly regulated against self-hosted infrastructure or requiring fully managed services. ## When NOT to use LeanCopilot - Working exclusively in theorem provers other than Lean or Lean4 - Looking for general-purpose AI programming assistant beyond Lean's domain ## Common questions ### What is the difference between forge and LeanCopilot? forge: A Python framework for self-hosted LLM tool-calling and multi-step agentic workflows. LeanCopilot: LLMs as Copilots for Theorem Proving in Lean. See the comparison table for live GitHub stats and shared categories. ### When should I choose forge over LeanCopilot? Choose forge over LeanCopilot when forge is primarily Python; LeanCopilot is C++; Requirements: Min 4 GB RAM; Requires Docker; Requires Python 3.12+ and a running LLM backend.; Can be set up with local backends (e.g., llama.cpp) or Anthropic via its API, requiring an API key for the latter case.; Tags unique to forge: agentic-ai, function-calling, multi-step-workflows, python-framework; - You require an agnostic backend setup, such as local LLM backends like llama.cpp or cloud-based services with Anthropic. ### When should I choose LeanCopilot over forge? Choose LeanCopilot over forge when LeanCopilot is primarily C++; forge is Python; Tags unique to LeanCopilot: formal-mathematics, lean, lean4, llm; Need support with formal proof development in Lean or Lean4 specifically. ### When should I avoid forge? - If your application does not require flexibility in backend selection, and you prefer a single cloud provider like Anthropic without local setup. - For scenarios where simplicity of setup outweighs the need for customization in function calling and workflow management. - When working within environments strictly regulated against self-hosted infrastructure or requiring fully managed services. ### When should I avoid LeanCopilot? Working exclusively in theorem provers other than Lean or Lean4 Looking for general-purpose AI programming assistant beyond Lean's domain ### Is forge or LeanCopilot more popular on GitHub? forge has more GitHub stars (2,217 vs 1,314). Stars measure visibility, not whether either tool fits your constraints. ### Are forge and LeanCopilot open source? Yes - both are open-source projects on GitHub (forge: MIT, LeanCopilot: MIT). ### Where can I find alternatives to forge or LeanCopilot? GraphCanon lists graph-backed alternatives at [forge alternatives](/tools/antoinezambelli-forge/alternatives) and [LeanCopilot alternatives](/tools/lean-dojo-leancopilot/alternatives) ([forge markdown twin](/tools/antoinezambelli-forge/alternatives.md), [LeanCopilot markdown twin](/tools/lean-dojo-leancopilot/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/antoinezambelli-forge-vs-lean-dojo-leancopilot.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, forge or LeanCopilot? forge: Very active. LeanCopilot: 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 forge and LeanCopilot? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [forge trust report](/tools/antoinezambelli-forge/trust); [LeanCopilot trust report](/tools/lean-dojo-leancopilot/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=antoinezambelli-forge`](/api/graphcanon/graph?tool=antoinezambelli-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/_