Z3/SMT MCP Server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Z3/SMT MCP Serversolve x + y = 10, x - y = 4 for integers"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Z3/SMT MCP Server
An MCP (Model Context Protocol) server that exposes Z3/SMT solver capabilities for constraint solving, logical reasoning, and satisfiability checking.
Features
Direct Z3 Python code execution - Run arbitrary Z3 Python code
SMT-LIB 2.0 support - Parse and solve SMT-LIB format problems
Constraint checking - Check satisfiability of constraint lists
Theorem proving - Prove theorems by showing unsatisfiability of negation
Expression simplification - Simplify Z3 expressions
Logic program solving - Parse and solve structured logic programs (Logic-LLM format)
Session management - Incremental solving with push/pop support
Installation
# Using pip
pip install z3smt-mcp
# Or install from source
git clone https://github.com/z3smt-mcp/z3smt-mcp
cd z3smt-mcp
pip install -e .Requirements
Python >= 3.10
z3-solver >= 4.12.0
mcp >= 1.0.0
Usage
Running the Server
# Run directly
z3smt-mcp
# Or via Python
python -m z3smt_mcp.serverClaude Desktop Configuration
Add to your Claude Desktop config (claude_desktop_config.json):
{
"mcpServers": {
"z3smt": {
"command": "z3smt-mcp"
}
}
}Or if installed from source:
{
"mcpServers": {
"z3smt": {
"command": "python",
"args": ["-m", "z3smt_mcp.server"]
}
}
}Available Tools
solve
Execute Z3 Python code directly. All Z3 imports are pre-loaded.
# Example: Solve a system of linear equations
x = Int('x')
y = Int('y')
solver = Solver()
solver.add(x + y == 10)
solver.add(x - y == 4)
if solver.check() == sat:
print(solver.model())
# Output: [y = 3, x = 7]solve_smtlib
Solve problems in SMT-LIB 2.0 format.
(declare-const x Int)
(declare-const y Int)
(assert (= (+ x y) 10))
(assert (= (- x y) 4))
(check-sat)
(get-model)check_sat
Check satisfiability of a list of constraints with automatic variable detection.
{
"constraints": ["x + y == 10", "x > 0", "y > 0", "x < y"]
}prove
Prove a theorem by showing its negation is unsatisfiable.
{
"theorem": "Implies(And(x > 0, y > 0), x + y > 0)",
"variables": {"x": "int", "y": "int"}
}simplify
Simplify a Z3 expression.
{
"expression": "And(x > 0, Or(x > 0, y > 0))"
}solve_logic_program
Solve structured logic programs in Logic-LLM format.
# Declarations
Color = EnumSort([red, green, blue])
assign = Function(Object -> Color)
# Constraints
assign(obj1) != assign(obj2)
Distinct([c:Color], assign(c))Session Management Tools
session_add_variable- Add a variable to the sessionsession_add_constraint- Add a constraint to the sessionsession_check- Check satisfiability and get modelsession_push- Push a new context (for backtracking)session_pop- Pop context (backtrack)session_reset- Clear the sessionlist_sessions- List all active sessions
Examples
Solving Sudoku
# Create a 9x9 grid of integer variables
X = [[Int(f"x_{i}_{j}") for j in range(9)] for i in range(9)]
solver = Solver()
# Each cell contains a value in 1-9
for i in range(9):
for j in range(9):
solver.add(And(X[i][j] >= 1, X[i][j] <= 9))
# Each row has distinct values
for i in range(9):
solver.add(Distinct(X[i]))
# Each column has distinct values
for j in range(9):
solver.add(Distinct([X[i][j] for i in range(9)]))
# Each 3x3 box has distinct values
for box_i in range(3):
for box_j in range(3):
box = [X[3*box_i + i][3*box_j + j]
for i in range(3) for j in range(3)]
solver.add(Distinct(box))
# Add known values (example)
solver.add(X[0][0] == 5)
solver.add(X[0][1] == 3)
# ... more constraints
if solver.check() == sat:
m = solver.model()
for i in range(9):
print([m[X[i][j]] for j in range(9)])Bit-Vector Arithmetic
# Solve for x where x * 3 == 21 in 8-bit arithmetic
x = BitVec('x', 8)
solver = Solver()
solver.add(x * 3 == 21)
if solver.check() == sat:
print(solver.model())Array Theory
# Find an array where a[0] + a[1] == 10
a = Array('a', IntSort(), IntSort())
solver = Solver()
solver.add(a[0] + a[1] == 10)
solver.add(a[0] > 0)
solver.add(a[1] > 0)
if solver.check() == sat:
print(solver.model())Credits
Z3 solver implementation adapted from Logic-LLM
MCP interface inspired by clingo-mcp
Z3 Theorem Prover by Microsoft Research
License
MIT License
Maintenance
Resources
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