GPT Research MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| OPENAI_API_KEY | Yes | Your OpenAI API key | |
| LANGFUSE_BASE_URL | No | LangFuse base URL (optional, for tracing). Use https://cloud.langfuse.com for EU region or https://us.cloud.langfuse.com for US region | |
| LANGFUSE_PUBLIC_KEY | No | Your LangFuse public key (optional, for tracing) | |
| LANGFUSE_SECRET_KEY | No | Your LangFuse secret key (optional, for tracing) |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| researchC | Ask questions, search for information, or consult about complex problems in English. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 1 tool
With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool 'research' has a clearly defined purpose, so an agent cannot misselect between non-existent alternatives.
A single tool inherently exhibits perfect naming consistency, as there are no other tools to compare it against for patterns or conventions. The name 'research' is straightforward and follows a simple verb-based naming style.
One tool is too few for a server named 'GPT Research MCP Server', which suggests a research-oriented domain that typically requires multiple operations (e.g., search, summarize, cite, query). A single tool feels thin and under-scoped for such a purpose, limiting functionality.
The tool surface is severely incomplete for a research server. While 'research' covers general inquiry, there are obvious gaps such as specialized search, result filtering, citation management, or data analysis tools that would be expected in this domain, likely causing agent failures in complex tasks.