Lean定理证明器
STDIOLean定理证明器交互MCP服务器
Lean定理证明器交互MCP服务器
MCP server that allows agentic interaction with the Lean theorem prover via the Language Server Protocol using leanclient. This server provides a range of tools for LLM agents to understand, analyze and interact with Lean projects.
LeanSearch, Loogle, Lean Finder, Lean Hammer and Lean State Search to find relevant theorems and definitions.lake build manually.rg) to reduce hallucinations using local search.Install uv for your system. On Linux/MacOS: curl -LsSf https://astral.sh/uv/install.sh | sh
lake buildlean-lsp-mcp will run lake serve in the project root to use the language server (for most tools). Some clients (e.g. Cursor) might timeout during this process. Therefore, it is recommended to run lake build manually before starting the MCP. This ensures a faster build time and avoids timeouts.
OR using the setup wizard:
Ctrl+Shift+P > "MCP: Add Server..." > "Command (stdio)" > "uvx lean-lsp-mcp" > "lean-lsp" (or any name you like) > Global or Workspace
OR manually adding config by opening mcp.json with:
Ctrl+Shift+P > "MCP: Open User Configuration"
and adding the following
{ "servers": { "lean-lsp": { "type": "stdio", "command": "uvx", "args": [ "lean-lsp-mcp" ] } } }
If you installed VSCode on Windows and are using WSL2 as your development environment, you may need to use this config instead:
{ "servers": { "lean-lsp": { "type": "stdio", "command": "wsl.exe", "args": [ "uvx", "lean-lsp-mcp" ] } } }
If that doesn't work, you can try cloning this repository and replace "lean-lsp-mcp" with "/path/to/cloned/lean-lsp-mcp".
"+ Add a new global MCP Server" > ("Create File")
Paste the server config into mcp.json file:
{ "mcpServers": { "lean-lsp": { "command": "uvx", "args": ["lean-lsp-mcp"] } } }
# Local-scoped MCP server claude mcp add lean-lsp uvx lean-lsp-mcp # OR project-scoped MCP server # (creates or updates a .mcp.json file in the current directory) claude mcp add lean-lsp -s project uvx lean-lsp-mcp
You can find more details about MCP server configuration for Claude Code here.
If you are using Claude Desktop or Claude Code, you can also install the Lean4 Theorem Proving Skill. This skill provides additional prompts and templates for interacting with Lean4 projects and includes a section on interacting with the lean-lsp-mcp server.
For the local search tool lean_local_search, install ripgrep (rg) and make sure it is available in your PATH.
Get the contents of a Lean file, optionally with line number annotations.
Get all diagnostic messages for a Lean file. This includes infos, warnings and errors.
l20c42-l20c46, severity: 1
simp made no progress
l21c11-l21c45, severity: 1
function expected at
  h_empty
term has type
  T ∩ compl T = ∅
...
Get the proof goal at a specific location (line or line & column) in a Lean file.
Before:
S : Type u_1
inst✝¹ : Fintype S
inst✝ : Nonempty S
P : Finset (Set S)
hPP : ∀ T ∈ P, ∀ U ∈ P, T ∩ U ≠ ∅
hPS : ¬∃ T ∉ P, ∀ U ∈ P, T ∩ U ≠ ∅
compl : Set S → Set S := fun T ↦ univ \ T
hcompl : ∀ T ∈ P, compl T ∉ P
all_subsets : Finset (Set S) := Finset.univ
h_comp_in_P : ∀ T ∉ P, compl T ∈ P
h_partition : ∀ (T : Set S), T ∈ P ∨ compl T ∈ P
⊢ P.card = 2 ^ (Fintype.card S - 1)
After:
no goals
Get the term goal at a specific position (line & column) in a Lean file.
Retrieve hover information (documentation) for symbols, terms, and expressions in a Lean file (at a specific line & column).
The `sorry` tactic is a temporary placeholder for an incomplete tactic proof,
closing the main goal using `exact sorry`.
This is intended for stubbing-out incomplete parts of a proof while still having a syntactically correct proof skeleton.
Lean will give a warning whenever a proof uses `sorry`, so you aren't likely to miss it,
but you can double check if a theorem depends on `sorry` by looking for `sorryAx` in the output
of the `#print axioms my_thm` command, the axiom used by the implementation of `sorry`.
Get the file contents where a symbol or term is declared.
Code auto-completion: Find available identifiers or import suggestions at a specific position (line & column) in a Lean file.
Run/compile an independent Lean code snippet/file and return the result or error message.
l1c1-l1c6, severity: 3
38
Attempt multiple lean code snippets on a line and return goal state and diagnostics for each snippet. This tool is useful to screen different proof attempts before using the most promising one.
  rw [Nat.pow_sub (Fintype.card_pos_of_nonempty S)]:
S : Type u_1
inst✝¹ : Fintype S
inst✝ : Nonempty S
P : Finset (Set S)
hPP : ∀ T ∈ P, ∀ U ∈ P, T ∩ U ≠ ∅
hPS : ¬∃ T ∉ P, ∀ U ∈ P, T ∩ U ≠ ∅
⊢ P.card = 2 ^ (Fintype.card S - 1)
l14c7-l14c51, severity: 1
unknown constant 'Nat.pow_sub'
  by_contra h_neq:
 S : Type u_1
inst✝¹ : Fintype S
inst✝ : Nonempty S
P : Finset (Set S)
hPP : ∀ T ∈ P, ∀ U ∈ P, T ∩ U ≠ ∅
hPS : ¬∃ T ∉ P, ∀ U ∈ P, T ∩ U ≠ ∅
h_neq : ¬P.card = 2 ^ (Fintype.card S - 1)
⊢ False
...
Search for Lean definitions and theorems in the local Lean project and stdlib. This is useful to confirm declarations actually exist and prevent hallucinating APIs.
This tool requires ripgrep (rg) to be installed and available in your PATH.
Currently most external tools are separately rate limited to 3 requests per 30 seconds. Please don't ruin the fun for everyone by overusing these amazing free services!
Please cite the original authors of these tools if you use them!
Search for theorems in Mathlib using leansearch.net (natural language search).
Github Repository | Arxiv Paper
bijective map from injective, n + 1 <= m if n < m, Cauchy Schwarz, List.sum, {f : A → B} (hf : Injective f) : ∃ h, Bijective h{ "module_name": "Mathlib.Logic.Function.Basic", "kind": "theorem", "name": "Function.Bijective.injective", "signature": " {f : α → β} (hf : Bijective f) : Injective f", "type": "∀ {α : Sort u_1} {β : Sort u_2} {f : α → β}, Function.Bijective f → Function.Injective f", "value": ":= hf.1", "informal_name": "Bijectivity Implies Injectivity", "informal_description": "For any function $f \\colon \\alpha \\to \\beta$, if $f$ is bijective, then $f$ is injective." }, ...
Search for Lean definitions and theorems using loogle.lean-lang.org.
Real.sin, "differ", _ * (_ ^ _), (?a -> ?b) -> List ?a -> List ?b, |- tsum _ = _ * tsum _[ { "type": " (x : ℝ) : ℝ", "name": "Real.sin", "module": "Mathlib.Data.Complex.Trigonometric" }, ... ]
Semantic search for Mathlib theorems using Lean Finder.
algebraic elements x,y over K with same minimal polynomial, Does y being a root of minpoly(x) imply minpoly(x)=minpoly(y)?, ⊢ |re z| ≤ ‖z‖ + transform to squared norm inequality, theorem restrict Ioi: restrict Ioi e = restrict Ici eQuery: Does y being a root of minpoly(x) imply minpoly(x)=minpoly(y)?
[ [ "/-- If `y : L` is a root of `minpoly K x`, then `minpoly K y = minpoly K x`. -/\ntheorem eq_of_root {x y : L} (hx : IsAlgebraic K x)\n (h_ev : Polynomial.aeval y (minpoly K x) = 0) : minpoly K y = minpoly K x :=\n ((eq_iff_aeval_minpoly_eq_zero hx.isIntegral).mpr h_ev).symm", "Let $L/K$ be a field extension, and let $x, y \\in L$ be elements such that $y$ is a root of the minimal polynomial of $x$ over $K$. If $x$ is algebraic over $K$, then the minimal polynomial of $y$ over $K$ is equal to the minimal polynomial of $x$ over $K$, i.e., $\\text{minpoly}_K(y) = \\text{minpoly}_K(x)$. This means that if $y$ satisfies the polynomial equation defined by $x$, then $y$ shares the same minimal polynomial as $x$." ], ... ]
Search for applicable theorems for the current proof goal using premise-search.com.
Github Repository | Arxiv Paper
A self-hosted version is available and encouraged. You can set an environment variable LEAN_STATE_SEARCH_URL to point to your self-hosted instance. It defaults to https://premise-search.com.
Uses the first goal at a given line and column. Returns a list of relevant theorems.
[ { "name": "Nat.mul_zero", "formal_type": "∀ (n : Nat), n * 0 = 0", "module": "Init.Data.Nat.Basic" }, ... ]
Search for relevant premises based on the current proof state using the Lean Hammer Premise Search.
Github Repository | Arxiv Paper
A self-hosted version is available and encouraged. You can set an environment variable LEAN_HAMMER_URL to point to your self-hosted instance. It defaults to http://leanpremise.net.
Uses the first goal at a given line and column. Returns a list of relevant premises (theorems) that can be used to prove the goal.
Note: We use a simplified version, LeanHammer might have better premise search results.
[ "MulOpposite.unop_injective", "MulOpposite.op_injective", "WellFoundedLT.induction", ... ]
Rebuild the Lean project and restart the Lean LSP server.
Many clients allow the user to disable specific tools manually (e.g. lean_build).
VSCode: Click on the Wrench/Screwdriver icon in the chat.
Cursor: In "Cursor Settings" > "MCP" click on the name of a tool to disable it (strikethrough).
This MCP server works out-of-the-box without any configuration. However, a few optional settings are available.
LEAN_LOG_LEVEL: Log level for the server. Options are "INFO", "WARNING", "ERROR", "NONE". Defaults to "INFO".LEAN_PROJECT_PATH: Path to your Lean project root. Set this if the server cannot automatically detect your project.LEAN_LSP_MCP_TOKEN: Secret token for bearer authentication when using streamable-http or sse transport.LEAN_STATE_SEARCH_URL: URL for a self-hosted premise-search.com instance.LEAN_HAMMER_URL: URL for a self-hosted Lean Hammer Premise Search instance.You can also often set these environment variables in your MCP client configuration:
{ "servers": { "lean-lsp": { "type": "stdio", "command": "uvx", "args": [ "lean-lsp-mcp" ], "env": { "LEAN_PROJECT_PATH": "/path/to/your/lean/project", "LEAN_LOG_LEVEL": "NONE" } } } }
The Lean LSP MCP server supports the following transport methods:
stdio: Standard input/output (default)streamable-http: HTTP streamingsse: Server-sent events (MCP legacy, use streamable-http if possible)You can specify the transport method using the --transport argument when running the server. For sse and streamable-http you can also optionally specify the host and port:
uvx lean-lsp-mcp --transport stdio # Default transport uvx lean-lsp-mcp --transport streamable-http # Available at http://127.0.0.1:8000/mcp uvx lean-lsp-mcp --transport sse --host localhost --port 12345 # Available at http://localhost:12345/sse
Transport via streamable-http and sse supports bearer token authentication. This allows publicly accessible MCP servers to restrict access to authorized clients.
Set the LEAN_LSP_MCP_TOKEN environment variable (or see section 3 for setting env variables in MCP config) to a secret token before starting the server.
Example Linux/MacOS setup:
export LEAN_LSP_MCP_TOKEN="your_secret_token" uvx lean-lsp-mcp --transport streamable-http
Clients should then include the token in the Authorization header.
There are many valid security concerns with the Model Context Protocol (MCP) in general!
This MCP server is meant as a research tool and is currently in beta. While it does not handle any sensitive data such as passwords or API keys, it still includes various security risks:
Please be aware of these risks. Feel free to audit the code and report security issues!
For more information, you can use Awesome MCP Security as a starting point.
npx @modelcontextprotocol/inspector uvx --with-editable path/to/lean-lsp-mcp python -m lean_lsp_mcp.server
uv sync --all-extras uv run pytest tests
MIT licensed. See LICENSE for more information.
Citing this repository is highly appreciated but not required by the license.
@software{lean-lsp-mcp, author = {Oliver Dressler}, title = {{Lean LSP MCP: Tools for agentic interaction with the Lean theorem prover}}, url = {https://github.com/oOo0oOo/lean-lsp-mcp}, month = {3}, year = {2025} }