Skip to main content
Glama
roberthamel

websearch-mcp

by roberthamel
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
LLM_MODELYesModel name for chat completions
VLM_MODELNoModel name for image description (defaults to LLM_MODEL)
LLM_API_KEYYesAPI key for the LLM endpoint
LLM_TIMEOUTNoLLM request timeout in seconds60
SEARXNG_URLYesBase URL of SearXNG instance
VLM_API_KEYNoAPI key for VLM endpoint (defaults to LLM_API_KEY)
LLM_BASE_URLYesOpenAI-compatible endpoint base URL
VLM_BASE_URLNoOpenAI-compatible endpoint for VLM (defaults to LLM_BASE_URL)
FETCH_TIMEOUTNoPer-page fetch timeout in seconds30
MAX_IMAGE_SIZENoMax image size in bytes (10MB)10485760
MAX_CONTENT_SIZENoMax content size in bytes (5MB)5242880
CACHE_MAX_ENTRIESNoMax cache entries before LRU eviction1000
CACHE_TTL_SECONDSNoCache TTL in seconds (0 to disable)900
DEFAULT_MAX_RESULTSNoDefault result count for web_search10

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

CapabilityDetails
tools
{
  "listChanged": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
web_searchA

Search the web using SearXNG, fetch top result pages, and synthesize with LLM.

Args:
    query: The search query string.
    max_results: Maximum number of results to return (default: 10).
    allowed_domains: Only include results from these domains.
    blocked_domains: Exclude results from these domains.
webfetchB

Fetch a single URL, extract content, and process with LLM.

Args:
    url: The URL to fetch.
    prompt: Optional instruction for LLM processing. If omitted, provides a general summary.
image_descriptionA

Describe an image using a vision language model.

Args:
    image: Either a base64-encoded string containing the image data,
           or an absolute filesystem path pointing to an image file.

Returns:
    JSON string with description, success status, and error info.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A3.7/5.0

Scored across 3 tools

Disambiguation5/5

Each tool has a clearly distinct purpose with no overlap: image_description handles visual analysis, webfetch processes single URLs, and web_search performs multi-result web searches. The boundaries are well-defined, preventing agent misselection.

Naming Consistency4/5

Two tools follow a consistent 'web_' prefix pattern (web_search, webfetch), but image_description deviates with a different naming convention. The naming is still readable and mostly predictable, with only minor inconsistency.

Tool Count4/5

Three tools is reasonable for a web search server, covering core functionalities (image analysis, URL fetching, web searches). It's slightly thin but well-scoped, with each tool earning its place without bloat.

Completeness3/5

The toolset covers key web search operations (searching, fetching, image analysis), but there are notable gaps like missing update/delete operations for saved searches or history management. Agents can work around this, but the surface is not fully comprehensive for extended workflows.

Resources