MCP server that exposes MiniZinc constraint solving and optimization to LLM clients like opencode, Claude Desktop, and Cursor
0
stars
15
commits
Python
primary language
Sep 15, 2026
updated
An MCP server that exposes MiniZinc constraint solving and optimization to LLM clients such as opencode, Claude Desktop, and Cursor. It lets an agent parse, type-check, and solve MiniZinc models directly from a chat session.
Built with the MCP Python SDK v2 and the MiniZinc Python binding.
Only two things need to be installed, once per machine:
curl -LsSf https://astral.sh/uv/install.sh | shminizinc executable on PATH (includes a default solver, Gecode)Everything else is fetched automatically by uv — there is no clone, no venv setup, and no manual pip install on your side.
Install it globally (best if you use it in several projects):
uv tool install --from git+https://github.com/carban/minizinc-mcp minizinc-mcp
Or run it on demand each time, with nothing installed:
uvx --from git+https://github.com/carban/minizinc-mcp minizinc-mcp
The server runs over stdio. Tell your MCP client to launch it:
opencode — project level (add this to opencode.jsonc in your project):
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"minizinc": {
"type": "local",
"command": ["uvx", "--from", "git+https://github.com/carban/minizinc-mcp", "minizinc-mcp"]
}
}
}
opencode — global (add the same mcp.minizinc block to ~/.config/opencode/opencode.json):
{
"mcp": {
"minizinc": {
"type": "local",
"command": ["uvx", "--from", "git+https://github.com/carban/minizinc-mcp", "minizinc-mcp"]
}
}
}
Claude Desktop (claude_desktop_config.json):
{
"mcpServers": {
"minizinc": {
"command": "uvx",
"args": ["--from", "git+https://github.com/carban/minizinc-mcp", "minizinc-mcp"]
}
}
}
Restart your client. Six tools should now be available, prefixed with minizinc_:
minizinc_list_solversminizinc_validate_modelminizinc_solve_modelminizinc_solve_model_by_pathminizinc_get_model_infominizinc_get_flatzincQuick sanity check — ask your client: "list the available MiniZinc solvers". You should see gecode, chuffed, highs, and anything else installed on the machine.
| Tool | Description |
|---|---|
list_solvers | Lists every MiniZinc solver installed on the machine. The returned tag names (e.g. gecode, chuffed, highs) can be passed to solve_model. |
validate_model | Parses and type-checks MiniZinc model code without solving it. Useful for checking model syntax up front. Returns VALID or INVALID with an error message. |
solve_model | Solves a MiniZinc model given as source code: once, exhaustively (all_solutions), or with a solution / time limit. Returns the status, solution(s), objective value (for optimization problems), and solver statistics. |
solve_model_by_path | Same as solve_model but loads the model and its optional data (.dzn) file from paths instead of source code. |
get_model_info | Inspects a model without solving it: returns its solve method (satisfy/minimize/maximize) and the declared input parameters and output variables with their types. Useful for an agent to know exactly which params a model expects. |
get_flatzinc | Compiles a model (and optional data) to FlatZinc text without solving it. Returns the .fzn model, the .ozn output model, and flattening statistics. Useful for debugging and low-level inspection. |
solve_model arguments| Argument | Type | Default | Description |
|---|---|---|---|
model_code | str | (required) | The MiniZinc source code (.mzn) of the model. |
params | dict | str | None | Parameter assignments like a .dzn file: a JSON object mapping names to values (a JSON string encoding such an object is also accepted). |
solver | str | "gecode" | Which solver to use (see list_solvers). |
all_solutions | bool | False | Compute all solutions of a solve satisfy problem. |
max_solutions | int | None | None | Stop after at most this many solutions. |
timeout_seconds | int | None | None | Solver time limit in seconds. |
The result is a JSON object like:
{
"status": "OPTIMAL_SOLUTION",
"objective": 9,
"solution": { "objective": 9, "x": 9, "y": 1 },
"statistics": { "time": 0.204, "nodes": 3, ... }
}
status is one of SATISFIED, OPTIMAL_SOLUTION, ALL_SOLUTIONS, UNSATISFIABLE, UNKNOWN, or ERROR. validate_model and solve_model never raise in normal operation — errors are returned inside the result dict.
Clone the repo, then:
uv sync # create the environment and install mcp + minizinc
The server speaks the MCP stdio transport, so it is launched as a subprocess by an MCP client. Run it with the SDK inspector:
uv run mcp dev server.py
that opens the MCP Inspector in the browser where every tool can be called interactively. A minimal programmatic smoke test:
uv run python -c "
import asyncio
from mcp import Client
from mcp.client.stdio import StdioServerParameters
async def main():
params = StdioServerParameters(command='uv', args=['run', 'python', 'server.py'], cwd='.')
async with Client(params) as client:
result = await client.call_tool('solve_model', {
'model_code': 'var 1..10: x; var 1..10: y; constraint x + y = 10; solve maximize x;'
})
print(result.content[0].text)
asyncio.run(main())
"
Install the test dependencies, then run the suite:
uv sync --group dev
uv run pytest -q
The tests in tests/ launch the server end-to-end over stdio and call every tool through the MCP protocol, solving the example model in example/. They need a working MiniZinc install (the same prerequisite as for developers).
params follows JSON representation: JSON arrays map to MiniZinc arrays; numbers, strings, and booleans map to their native MiniZinc types. Exotic types like sets and enums are not fully expressible this way.all_solutions with max_solutions; the MiniZinc driver rejects the combination.chuffed/gecode for CP, highs/cbc for MIP models). Use list_solvers to see what is installed.read_only_hint is set on all tools, so they do not modify your files or system.15 commits
Python
90.2%
MiniZinc
9.8%
MCP server that exposes MiniZinc constraint solving and optimization to LLM clients like opencode, Claude Desktop, and Cursor
0
stars
15
commits
Python
primary language
Sep 15, 2026
updated
An MCP server that exposes MiniZinc constraint solving and optimization to LLM clients such as opencode, Claude Desktop, and Cursor. It lets an agent parse, type-check, and solve MiniZinc models directly from a chat session.
Built with the MCP Python SDK v2 and the MiniZinc Python binding.
Only two things need to be installed, once per machine:
curl -LsSf https://astral.sh/uv/install.sh | shminizinc executable on PATH (includes a default solver, Gecode)Everything else is fetched automatically by uv — there is no clone, no venv setup, and no manual pip install on your side.
Install it globally (best if you use it in several projects):
uv tool install --from git+https://github.com/carban/minizinc-mcp minizinc-mcp
Or run it on demand each time, with nothing installed:
uvx --from git+https://github.com/carban/minizinc-mcp minizinc-mcp
The server runs over stdio. Tell your MCP client to launch it:
opencode — project level (add this to opencode.jsonc in your project):
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"minizinc": {
"type": "local",
"command": ["uvx", "--from", "git+https://github.com/carban/minizinc-mcp", "minizinc-mcp"]
}
}
}
opencode — global (add the same mcp.minizinc block to ~/.config/opencode/opencode.json):
{
"mcp": {
"minizinc": {
"type": "local",
"command": ["uvx", "--from", "git+https://github.com/carban/minizinc-mcp", "minizinc-mcp"]
}
}
}
Claude Desktop (claude_desktop_config.json):
{
"mcpServers": {
"minizinc": {
"command": "uvx",
"args": ["--from", "git+https://github.com/carban/minizinc-mcp", "minizinc-mcp"]
}
}
}
Restart your client. Six tools should now be available, prefixed with minizinc_:
minizinc_list_solversminizinc_validate_modelminizinc_solve_modelminizinc_solve_model_by_pathminizinc_get_model_infominizinc_get_flatzincQuick sanity check — ask your client: "list the available MiniZinc solvers". You should see gecode, chuffed, highs, and anything else installed on the machine.
| Tool | Description |
|---|---|
list_solvers | Lists every MiniZinc solver installed on the machine. The returned tag names (e.g. gecode, chuffed, highs) can be passed to solve_model. |
validate_model | Parses and type-checks MiniZinc model code without solving it. Useful for checking model syntax up front. Returns VALID or INVALID with an error message. |
solve_model | Solves a MiniZinc model given as source code: once, exhaustively (all_solutions), or with a solution / time limit. Returns the status, solution(s), objective value (for optimization problems), and solver statistics. |
solve_model_by_path | Same as solve_model but loads the model and its optional data (.dzn) file from paths instead of source code. |
get_model_info | Inspects a model without solving it: returns its solve method (satisfy/minimize/maximize) and the declared input parameters and output variables with their types. Useful for an agent to know exactly which params a model expects. |
get_flatzinc | Compiles a model (and optional data) to FlatZinc text without solving it. Returns the .fzn model, the .ozn output model, and flattening statistics. Useful for debugging and low-level inspection. |
solve_model arguments| Argument | Type | Default | Description |
|---|---|---|---|
model_code | str | (required) | The MiniZinc source code (.mzn) of the model. |
params | dict | str | None | Parameter assignments like a .dzn file: a JSON object mapping names to values (a JSON string encoding such an object is also accepted). |
solver | str | "gecode" | Which solver to use (see list_solvers). |
all_solutions | bool | False | Compute all solutions of a solve satisfy problem. |
max_solutions | int | None | None | Stop after at most this many solutions. |
timeout_seconds | int | None | None | Solver time limit in seconds. |
The result is a JSON object like:
{
"status": "OPTIMAL_SOLUTION",
"objective": 9,
"solution": { "objective": 9, "x": 9, "y": 1 },
"statistics": { "time": 0.204, "nodes": 3, ... }
}
status is one of SATISFIED, OPTIMAL_SOLUTION, ALL_SOLUTIONS, UNSATISFIABLE, UNKNOWN, or ERROR. validate_model and solve_model never raise in normal operation — errors are returned inside the result dict.
Clone the repo, then:
uv sync # create the environment and install mcp + minizinc
The server speaks the MCP stdio transport, so it is launched as a subprocess by an MCP client. Run it with the SDK inspector:
uv run mcp dev server.py
that opens the MCP Inspector in the browser where every tool can be called interactively. A minimal programmatic smoke test:
uv run python -c "
import asyncio
from mcp import Client
from mcp.client.stdio import StdioServerParameters
async def main():
params = StdioServerParameters(command='uv', args=['run', 'python', 'server.py'], cwd='.')
async with Client(params) as client:
result = await client.call_tool('solve_model', {
'model_code': 'var 1..10: x; var 1..10: y; constraint x + y = 10; solve maximize x;'
})
print(result.content[0].text)
asyncio.run(main())
"
Install the test dependencies, then run the suite:
uv sync --group dev
uv run pytest -q
The tests in tests/ launch the server end-to-end over stdio and call every tool through the MCP protocol, solving the example model in example/. They need a working MiniZinc install (the same prerequisite as for developers).
params follows JSON representation: JSON arrays map to MiniZinc arrays; numbers, strings, and booleans map to their native MiniZinc types. Exotic types like sets and enums are not fully expressible this way.all_solutions with max_solutions; the MiniZinc driver rejects the combination.chuffed/gecode for CP, highs/cbc for MIP models). Use list_solvers to see what is installed.read_only_hint is set on all tools, so they do not modify your files or system.15 commits
Python
90.2%
MiniZinc
9.8%