gpt-researcher-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| FAST_LLM | Yes | Fast LLM model, e.g., google_genai:gemini-1.5-flash | |
| EMBEDDING | Yes | Embedding model, e.g., google_genai:models/text-embedding-004 | |
| SMART_LLM | Yes | Smart LLM model, e.g., google_genai:gemini-1.5-pro | |
| llm_provider | Yes | LLM provider, e.g., google_genai | |
| STRATEGIC_LLM | Yes | Strategic LLM model, e.g., google_genai:gemini-1.5-pro | |
| GOOGLE_API_KEY | Yes | Google API key | |
| TAVILY_API_KEY | Yes | Tavily API key |
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
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| add-noteC | Add a new note |
| get_reportC | Get a research report based on a query and report type |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| summarize-notes | Creates a summary of all notes |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 2 tools
The two tools, add-note and get_report, have completely distinct purposes with no overlap. An agent can easily tell them apart based on their names and descriptions.
Both tool names follow a consistent verb_noun pattern using hyphens (add-note, get-report). This is a clear and predictable naming convention.
With only two tools, the server feels thin and borderline under-scoped for a research-focused MCP server. Two tools fall into the lower end of acceptable range but do not feel entirely insufficient.
The server lacks core operations for a research workflow, such as initiating research, listing past reports, or managing notes beyond adding. Significant gaps exist that would likely cause agent failures in practical use.