URL-Context-MCP MCP
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| GOOGLE_API_KEY | Yes | Your Gemini API key from Google AI for Developers |
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 |
|---|---|
| analyze_urlsC | Analyze and summarize the content of given URLs using Google Gemini URL Context. Provide an optional instruction and model. |
| google_searchB | Search the web using Google Search grounding via Gemini API. Provides search results with sources and citations. |
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 2 tools
The two tools have clearly distinct purposes: analyze_urls is for summarizing content from specific URLs, while google_search is for performing web searches to find information. There is no overlap in functionality, making it easy for an agent to choose the correct tool based on the task.
Both tool names follow a consistent verb_noun pattern (analyze_urls, google_search) with clear, descriptive verbs and nouns. The naming style is uniform and predictable across the set.
With only 2 tools, the server feels under-scoped for a URL and search context MCP. While the tools cover basic analysis and search, the lack of additional operations (e.g., URL validation, result filtering, or advanced search options) limits functionality and may require agents to work around gaps.
The tool set is severely incomplete for a URL and search domain. It lacks essential operations such as URL validation, content extraction beyond summarization, search result refinement, or integration with other web tools. This will likely cause agent failures when handling more complex tasks.