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mcp-pyright

mcp-pyright

by daedalus
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

get_completions

Retrieve Python code completion suggestions at a specific cursor position to help developers write code more efficiently by providing relevant options based on context.

Instructions

Get code completions at a specific position.

Returns available completions at the given cursor position.

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>",
      "position": "<position>"
    },
    "name": "get_completions"
  }
}

Input Schema

NameRequiredDescriptionDefault
codeYesPython code as string.
positionYesCharacter position (0-indexed) in the code.
python_pathNoOptional path to Python interpreter.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
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 of behavioral disclosure. It states the tool 'Returns available completions' but doesn't explain what 'completions' entail (e.g., suggestions, snippets), how they're generated, potential limitations (e.g., language support, accuracy), or response format. 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.

Conciseness4/5

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

The description is concise with two sentences that directly state the purpose and return value. It's front-loaded with the core action and avoids unnecessary details. However, the second sentence slightly repeats the first ('Get code completions' vs. 'Returns available completions'), making it marginally less efficient than a perfectly streamlined version.

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

Completeness3/5

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

Given the tool's moderate complexity (code analysis), no annotations, and an output schema (which handles return values), the description is minimally adequate. It covers the basic purpose but lacks behavioral context (e.g., how completions work) and usage guidelines. With the output schema, completeness isn't severely lacking, but it doesn't fully compensate for the missing annotations.

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?

Schema description coverage is 100%, so the schema already documents all three parameters ('code', 'position', 'python_path') with clear descriptions. The description adds no additional parameter semantics beyond implying position-based completion, which the schema's 'position' description ('Character position in the code') already covers. This meets the baseline for high schema coverage.

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 tool's purpose: 'Get code completions at a specific position' specifies the verb ('Get'), resource ('code completions'), and scope ('at a specific position'). However, it doesn't explicitly differentiate from sibling tools like 'get_definition' or 'get_hover', which might also operate on code positions, so it lacks sibling differentiation for a perfect score.

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 sibling tools like 'check_types' or 'format_code', nor does it specify prerequisites or exclusions. The agent must infer usage from the purpose alone, which is insufficient for effective tool 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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