Skip to main content
Glama
enesjakozh
pierrebrunelle

OpenAI MCP Server

by pierrebrunelle
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

OpenAI MCP Server

Query OpenAI models directly from Claude using MCP protocol.

preview

Setup

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "openai-server": {
      "command": "python",
      "args": ["-m", "src.mcp_server_openai.server"],
      "env": {
        "PYTHONPATH": "C:/path/to/your/mcp-server-openai",
        "OPENAI_API_KEY": "your-key-here"
      }
    }
  }
}

Related MCP server: OpenAI MCP Server

Development

git clone https://github.com/pierrebrunelle/mcp-server-openai
cd mcp-server-openai
pip install -e .

Testing

# Run tests from project root
pytest -v test_openai.py -s

# Sample test output:
Testing OpenAI API call...
OpenAI Response: Hello! I'm doing well, thank you for asking...
PASSED

License

MIT License

Available Tools

1 tool
ask-openaiC

Ask my assistant models a direct question

ParametersJSON Schema
NameRequiredDescriptionDefault
queryYesAsk assistant
modelNogpt-4
temperatureNo
max_tokensNo

TDQS

C2.4/5.0
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 mentions 'ask' and 'direct question,' implying a read-only query, but fails to detail authentication needs, rate limits, response format, or potential costs. This is a significant gap for an AI interaction tool with no annotation coverage.

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, efficient sentence with no wasted words, making it appropriately concise. However, it lacks front-loading of critical information, as it doesn't immediately clarify the tool's core function beyond a vague phrase.

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 interacting with AI models, no annotations, no output schema, and low schema coverage, the description is incomplete. It doesn't address behavioral traits, parameter meanings, or expected outputs, leaving the agent under-informed for effective tool use.

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?

Schema description coverage is low at 25%, with only the 'query' parameter having a minimal description ('Ask assistant'). The tool description adds no parameter semantics beyond what the schema provides, failing to compensate for the coverage gap. It doesn't explain the purpose of model selection, temperature, or max_tokens.

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 'Ask my assistant models a direct question' states a purpose (asking questions to AI models) but is vague about what 'assistant models' refers to and lacks specificity about the resource or scope. It doesn't distinguish from siblings (none exist), but the phrasing is somewhat unclear rather than tautological.

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, prerequisites, or exclusions. It merely states what the tool does without context for application, leaving the agent to infer usage scenarios.

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

Install Server
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

TDQS

C2.7/5.0
Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap between tools. The tool 'ask-openai' has a clear and singular purpose, making it impossible for an agent to misselect between tools.

Naming Consistency5/5

Since there is only one tool, naming consistency is inherently perfect. The tool name 'ask-openai' follows a verb_noun pattern, and with no other tools to compare against, there are no inconsistencies.

Tool Count2/5

A single tool is generally too few for a server's purpose, as it limits functionality and scope. For an 'OpenAI MCP Server', one might expect more comprehensive coverage such as different model interactions, fine-tuning, or other API endpoints, making this feel thin and under-scoped.

Completeness1/5

The tool set is severely incomplete for an 'OpenAI MCP Server'. With only a direct question tool, it lacks essential operations like model listing, chat completions, embeddings, or file handling, which are core to OpenAI's API. This will likely cause agent failures due to missing functionality.

Maintenance

ActivityInactive
ResponsivenessSyncing

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Related MCP Connectors

Related MCP Servers

  • OpenAI MCP Server

    thadius83
    A
    license
    C
    quality
    D
    maintenance
    Enables integration with OpenAI models through the MCP protocol, supporting concise and detailed responses for use with Claude Desktop.
    1
    3
    MIT

  • GPT-MCP Bridge

    bzzimmy
    F
    license
    Not graded
    quality
    Not graded
    maintenance
    Enables Claude and other MCP-compatible tools to communicate with OpenAI's GPT models (GPT-5, GPT-5-mini, o3) with conversation history and session management. Features advanced controls like reasoning effort settings, token tracking, and parallel conversation sessions for efficient AI workflows.
    10

Appeared in Searches

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/pierrebrunelle/mcp-server-openai'

If you have feedback or need assistance with the MCP directory API, please join our Discord server