Skip to main content
Glama
Sign In
ballerina-activemq-mcp-server

ballerina-activemq-mcp-server

by PasinduGunarathne
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

Deploy (run) Ballerina project

mq_deploy_project

Deploy a scaffolded Ballerina project as a detached background process, monitor for early crashes, and return its PID and optional service URL.

Instructions

Run bal run for a scaffolded project as a detached background process and return its PID. Watches the process for wait_ms to catch an early crash (and report the output) before declaring it started. If service_port is given, also returns a composed service URL. The process keeps running after this call returns. Verifies the Ballerina toolchain first.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "project_path": "<project_path>"
    },
    "name": "mq_deploy_project"
  }
}

Input Schema

NameRequiredDescriptionDefault
wait_msNoHow long to watch the process for an early crash before reporting it started (default 4000 ms).
project_pathYesAbsolute or ~/%USERPROFILE%-relative path to an existing scaffolded project root (the folder containing Ballerina.toml).
service_portNoOptional HTTP/observability port the running program exposes; used only to compose the returned service URL.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.7/5.0
Behavior5/5

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

The description richly discloses behavior: returns PID, watches for early crash for wait_ms, reports output, composes service URL if service_port given, and reveals that the process keeps running after return. This goes well beyond the annotations (readOnlyHint=false, idempotentHint=false) and adds critical operational context.

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

Conciseness5/5

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

Four sentences, each adds distinct value. Front-loaded with the core action, then behavior, optional output, and persistence. No fluff or redundancy.

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

Completeness5/5

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

Despite no output schema, the description explains the return values (PID, optional service URL) and the asynchronous nature of the process. It also notes toolchain verification, making it complete for an agent to invoke correctly.

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

Parameters4/5

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

Schema covers all parameters (100% coverage), but the description adds context by explaining the functional role of wait_ms (watch for early crash) and service_port (compose service URL), enhancing the schema descriptions. Baseline is 3, and this pushes to 4.

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

Purpose5/5

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

The description states the specific action: 'Run `bal run` for a scaffolded project as a detached background process and return its PID.' It clearly distinguishes from sibling tools like mq_build_project (build) and mq_scaffold_project (scaffold) by focusing on deployment/execution.

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

Usage Guidelines4/5

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

The description implies usage after scaffolding and references a scaffolded project, but does not explicitly contrast with alternatives like mq_build_project or state when-not to use. It provides context (detached process, verifies toolchain) but lacks explicit exclusions or alternative guidance.

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

Deploy Server

Other Tools