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bschoepke

ableton-live-mcp

by bschoepke

live_call

Execute a method on an Ableton Live object by providing its reference, method name, and optional arguments to control the DAW.

Instructions

Call one Live object method.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
refYes
methodYes
argsNo
kwargsNo
timeoutNoSeconds to wait for Live's main thread.
expected_set_signatureNo

Implementation Reference

  • The actual handler that executes the 'live_call' tool: resolves a Live object by ref, gets the attribute by method name, and calls it with args/kwargs.
    def _rpc_call(self, params):
        obj = self._resolve(params.get("ref"))
        fn = getattr(obj, params["method"])
        return fn(*(params.get("args") or []), **(params.get("kwargs") or {}))
  • src/server.py:85-91 (registration)
    Registration of the 'live_call' tool with its input schema on the MCP server.
    server.add_tool(Tool("live_call", "Call one Live object method.", schema({
        "ref": ref,
        "method": {"type": "string"},
        "args": {"type": "array"},
        "kwargs": {"type": "object"},
        **mutation_controls,
    }, ["ref", "method"]), forward("call")))
  • Input schema for 'live_call': requires ref (path/id) and method string, accepts optional args array and kwargs object.
    server.add_tool(Tool("live_call", "Call one Live object method.", schema({
        "ref": ref,
        "method": {"type": "string"},
        "args": {"type": "array"},
        "kwargs": {"type": "object"},
        **mutation_controls,
    }, ["ref", "method"]), forward("call")))
  • The 'forward' helper that creates a lambda bridging the tool call to the bridge client's request method with the bridge method name 'call'.
    def forward(method: str):
        return lambda args: bridge.request(method, args)
    
    ref = {
        "type": "object",
        "properties": {
            "path": {"type": "string"},
            "id": {"type": "integer"},
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so the description should disclose behavioral traits (e.g., thread blocking, authorization needs, side effects). The minimal description 'Call one Live object method' provides no such information, leaving the agent uninformed about important runtime behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise (7 words), which is good for brevity but comes at the cost of missing essential information. It is not well-structured for quick consumption as it lacks a definition of the tool's role relative to siblings.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (6 parameters, nested objects, no output schema, no annotations) and lack of sibling differentiation, the description is grossly incomplete. It fails to equip the AI agent with enough context to use the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Only 17% of parameters have descriptions in the schema ('timeout' described); the description adds no parameter meaning. 'ref', 'method', 'args', 'kwargs', 'expected_set_signature' are left entirely to inference from names, making correct invocation difficult.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Call') and target ('one Live object method'), indicating a remote procedure invocation. However, it does not differentiate from siblings like live_eval or live_exec, which also invoke methods or code.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives such as live_eval, live_exec, or live_set. The description lacks context for the AI agent to choose correctly among many similar tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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