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Finance MCP

Finance MCP

by FlowLLM-AI
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

execute_code

Run Python code for financial analysis and calculations to support research workflows, with results output via print statements.

Instructions

Execute python code can be used in scenarios such as analysis or calculation, and the final result can be printed using the print function.

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": {
      "code": "<code>"
    },
    "name": "execute_code"
  }
}

Input Schema

NameRequiredDescriptionDefault
codeYescode to be executed

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.6/5.0
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. It mentions that results can be printed using `print`, but doesn't disclose critical behavioral traits such as execution environment, safety risks (e.g., code injection), permissions needed, timeouts, or output handling. This leaves significant gaps for a tool that executes arbitrary code.

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

Conciseness4/5

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

The description is a single sentence that is reasonably concise and front-loaded with the main action. However, it could be more structured by separating usage guidance from behavioral details, and the phrasing 'can be used in scenarios such as' is slightly verbose without adding much clarity.

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 the complexity of executing arbitrary code, no annotations, and no output schema, the description is incomplete. It lacks essential context such as execution environment, error handling, security implications, and what the return values or outputs look like beyond printing. This is inadequate for a tool with significant behavioral implications.

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

Parameters3/5

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

The input schema has 100% description coverage, with the 'code' parameter documented as 'code to be executed'. The description adds minimal value by implying Python code and the use of `print`, but doesn't provide additional syntax, format details, or constraints beyond what the schema already states. Baseline 3 is appropriate given high schema coverage.

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 states the tool 'Execute python code' and mentions scenarios like 'analysis or calculation', which provides a general purpose. However, it doesn't clearly distinguish this from sibling tools like 'execute_shell' or 'history_calculate', and the phrasing is somewhat vague rather than specific about what exactly gets executed or how.

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 mentions scenarios such as 'analysis or calculation' but provides no explicit guidance on when to use this tool versus alternatives like 'execute_shell' or 'history_calculate'. There's no mention of prerequisites, exclusions, or specific contexts that would help an agent choose correctly among siblings.

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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