Skip to main content
Glama
Peteroooooooo

multi-api-web-search

by Peteroooooooo
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Remote

Server Quality Checklist

50%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v2.3.0

  • Disambiguation1/5

    Both tools have the exact same description and purpose, differing only in the name prefix. An agent cannot reliably choose between them because they appear to be identical duplicates.

    Naming Consistency2/5

    Both names use snake_case, but 'web_search' and 'multi_api_web_search' are near-duplicates with no clear convention. The prefixed variant is inconsistent with the generic one, making the naming feel redundant rather than patterned.

    Tool Count2/5

    Two tools exist but they appear to serve the exact same function. One tool would be appropriate for this simple search server; the extra tool is redundant and does not earn its place.

    Completeness5/5

    For a web search server, the tool surface covers the core capability of performing live internet searches. No additional operations like create, update, or delete are relevant to this domain, so there are no obvious gaps.

  • Average 3.1/5 across 2 of 2 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 3 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available

  • Add a LICENSE file by following GitHub's guide. Once GitHub recognizes the license, the system will automatically detect it within a few hours.

    If the license does not appear after some time, you can manually trigger a new scan using the MCP server admin interface.

    MCP servers without a LICENSE cannot be installed.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

  • Add a glama.json file to provide metadata about your server.

  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

    {
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}

    Then . Browse examples.

  • Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior2/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    No annotations are present, so the description carries the full burden of behavioral disclosure. It states that the search is live and may span multiple configured API models, but it does not describe result format, failure behavior, rate limits, or what hybrid consensus actually returns. This is minimal behavioral transparency.

    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 front-loaded sentence with no filler. It communicates the core capability efficiently, though it omits deeper usage guidance that would have made it more complete.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness3/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    For a simple three-parameter search tool, the minimum invocation is well covered by the schema and the live-search statement. However, with no output schema and no annotations, the absence of result-format details and the lack of distinction from the sibling tool leave notable gaps.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters3/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema description coverage is 100%, so the schema already documents all three parameters adequately. The description adds the idea of hybrid consensus but does not meaningfully extend parameter semantics beyond the schema. Baseline 3 is appropriate.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose4/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly identifies a live web search action and explains single-model vs hybrid consensus modes. It names the resource and action, making the tool's purpose understandable. However, it doesn't distinguish this tool from sibling multi_api_web_search, especially since the description itself says 'Multi-API'.

    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?

    There is no explicit guidance on when to use web_search versus multi_api_web_search, and the sibling is not mentioned. The only usage signal is that 'hybrid' enables multi-engine consensus, which implies a mode choice but not when this tool should be preferred over an alternative.

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

  • Behavior3/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    With no annotations, the description carries the behavioral disclosure burden. It does convey that this performs live external searches and can aggregate multiple engines into a consensus, but it omits operational traits like rate limits, failure behavior, and unconfigured model handling.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is two tight sentences with no filler. The core operation is front-loaded, and the second sentence adds meaningful scope about single-model and hybrid consensus.

    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 no annotations, no output schema, and a sibling tool to differentiate from, the description is incomplete. It does not clarify default model behavior, expected result shape, or when to use this tool instead of web_search.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters3/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema coverage is 100%, so the schema already documents all parameters. The description adds no real parameter semantics beyond restating the hybrid mode that is already described in the model parameter.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose4/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description states a specific operation: live internet search across configured API models, with an optional hybrid consensus mode. It is clear and distinct from a vague generic search, but it does not explicitly position itself against the sibling web_search tool.

    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?

    There is no guidance on when to choose this tool over web_search, nor when to prefer single-model vs hybrid mode. The mention of hybrid implies a capability but does not provide selection criteria.

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

GitHub Badge

Glama performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

multi-api-web-search-mcp MCP server

Copy to your README.md:

Score Badge

multi-api-web-search-mcp MCP server

Copy to your README.md:

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/Peteroooooooo/multi-api-web-search-mcp'

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