Wraps the Z3 theorem prover so you can solve constraint satisfaction and optimization problems through MCP tools. Create Boolean, integer, and real variables, add constraints in a straightforward string syntax, then call solve or optimize to get satisfying assignments. The factorization example shows the flavor: define two integer variables p and q, constrain their product to equal a target number, add bounds and parity checks, and let Z3 find the factors. Useful when you need symbolic math solving, SMT queries, or constraint-based search without writing Python scripts directly. Each solver session maintains state across calls until you reset it.
MCP server exposing Z3 solver API
pip install mcp-z3-prover
from mcp_z3_prover import mcp
# Run the server
mcp.run()
Or from command line:
mcp-z3-prover
The server exposes the following tools:
# Create variables
create_int_var("x")
create_int_var("y")
# Add constraints
add_constraint("int:x + int:y == 10")
add_constraint("int:x > 0")
add_constraint("int:y > 0")
# Solve
result = solve()
# Returns: {"status": "sat", "model": {"x": "5", "y": "5"}}
# Get specific values
x_val = get_model_value("int:x")
# Factor n = 4295229443 where n = p * q with q <= sqrt(n)
create_int_var("p")
create_int_var("q")
# Add constraints
add_constraint("int:p * int:q == 4295229443")
add_constraint("4295229443 > int:p")
add_constraint("4295229443 > int:q")
add_constraint("int:q <= 65537") # sqrt(4295229443) ≈ 65537
add_constraint("int:q > 1")
add_constraint("int:p > 1")
add_constraint("int:q % 2 != 0") # q is odd
add_constraint("int:p % 2 != 0") # p is odd
# Solve
result = solve()
# Returns: {"status": "sat", "model": {"p": "65539", "q": "65537"}}
# Verification: 65537 * 65539 = 4295229443
git clone https://github.com/daedalus/mcp-z3-prover.git
cd mcp-z3-prover
pip install -e ".[test]"
# run tests
pytest
# format
ruff format src/ tests/
# lint
ruff check src/ tests/
# type check
mypy src/
mcp-name: io.github.daedalus/mcp-z3-prover