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Ledger CLI MCP Server

by minhyeoky

ledger_commodities

List and filter financial commodities using regex patterns for efficient data analysis within the Ledger CLI MCP Server, simplifying financial reporting and accounting tasks.

Instructions

List all commodities

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Implementation Reference

  • main.py:209-215 (handler)
    The main handler function for the 'ledger_commodities' tool. It builds the command list for 'ledger commodities' with an optional query filter and calls the run_ledger helper to execute it.
    def ledger_commodities(params: LedgerCommodities) -> str:
        cmd = ["commodities"]
    
        if params.query:
            cmd.append(params.query)
    
        return run_ledger(cmd)
  • main.py:66-69 (schema)
    Pydantic BaseModel schema defining the input parameters for the ledger_commodities tool, featuring an optional query string.
    class LedgerCommodities(BaseModel):
        query: Optional[str] = Field(
            None, description="Filter commodities by regex pattern"
        )
  • main.py:208-208 (registration)
    FastMCP decorator that registers the ledger_commodities function as a tool with the description 'List all commodities'.
    @mcp.tool(description="List all commodities")
  • Shared helper function that safely executes ledger CLI commands via subprocess, handling errors and input validation. Used by the ledger_commodities handler.
    def run_ledger(args: List[str]) -> str:
        try:
            if not LEDGER_FILE:
                return "Ledger file path not set. Please provide it via --ledger-file argument or LEDGER_FILE environment variable."
    
            # Validate inputs to prevent command injection
            for arg in args:
                if ";" in arg or "&" in arg or "|" in arg:
                    return "Error: Invalid characters in command arguments."
    
            result = subprocess.run(
                ["ledger", "-f", LEDGER_FILE] + args,
                check=True,
                text=True,
                capture_output=True,
            )
            return result.stdout
        except subprocess.CalledProcessError as e:
            error_message = f"Ledger command failed: {e.stderr}"
            if "couldn't find file" in e.stderr:
                error_message = f"Ledger file not found at {LEDGER_FILE}. Please provide a valid path via --ledger-file argument or LEDGER_FILE environment variable."
            return error_message
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'List all commodities' implies a read-only operation, but it doesn't specify if it's safe, if there are rate limits, pagination, or what the output format looks like. For a tool with no annotations, this leaves significant behavioral gaps.

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?

The description is extremely concise with just three words, front-loaded and free of unnecessary details. It efficiently communicates the core action without waste, making it easy to parse quickly.

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

Completeness2/5

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

Given no annotations, no output schema, and low schema description coverage, the description is incomplete. It doesn't explain what 'commodities' are in this context, how results are returned, or any constraints, making it inadequate for a tool that likely interacts with a ledger system.

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?

The input schema has 1 parameter with 0% description coverage in the schema itself, and the tool description doesn't mention any parameters. The description fails to compensate for the lack of schema documentation, leaving the 'query' parameter's purpose and usage unclear beyond what's minimally inferred from the schema.

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

Purpose3/5

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

The description 'List all commodities' clearly states the verb ('List') and resource ('commodities'), making the purpose understandable. However, it doesn't differentiate this tool from its siblings (like ledger_accounts or ledger_payees) which likely also list different resource types, so it's adequate but lacks sibling distinction.

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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention context, prerequisites, or exclusions, leaving the agent to infer usage based on the tool name alone, which is insufficient for effective selection.

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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