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The Daily Workflow — AI Tools & Free Alternatives

by com.thedailyworkflow
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search_mcp_servers

Read-onlyIdempotent

Search the catalog of 3500+ MCP servers at thedailyworkflow.com.

Args:
    query: Free-text search (matches name, description, keywords). Example: "notion", "postgres database".
    category: Filter by category. Common values: databases, web, filesystem, cloud,
              productivity, communication, dev, ai, search, monitoring.
    client: Filter by supported MCP client. Values: claude-desktop, cursor, cline,
            windsurf, continue, goose.
    language: Filter by implementation language. Values: typescript, python, go, rust, java.
    limit: Max results to return (1-25, default 10).

Returns:
    Dict with `count` and `results` (list of MCP server summaries).
    Each result has: slug, name, description, categories, language, transport,
    supported_clients, stars, repo_url, page_url (link to full info).

Use this when the user asks for an MCP server matching some need ("find me an MCP for X",
"what MCP servers work with Cursor", "Slack MCP servers"). After choosing a candidate,
call get_mcp_install_config to get ready-to-paste setup.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "search_mcp_servers"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoMaximum number of results to return (1-25; values outside the range are clamped). Default: 10.
queryNoFree-text search query matched against MCP server name, description and keywords. Example: "notion", "postgres database". Empty string returns unfiltered results.
clientNoFilter by supported MCP client. One of: "claude-desktop", "cursor", "cline", "windsurf", "continue", "goose". Empty string means any client.
categoryNoFilter by MCP server category. Common values: "databases", "web", "filesystem", "cloud", "productivity", "communication", "dev", "ai", "search", "monitoring". Empty string means any category.
languageNoFilter by implementation language of the MCP server. One of: "typescript", "python", "go", "rust", "java". Empty string means any language.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, non-destructive behavior, and the description adds useful context: catalog scale, what fields the query matches, and the return structure (count + results with slug, stars, repo_url, page_url). It stops short of describing result ordering or relevance/ranking behavior, which would help an agent interpret truncated results.

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?

Front-loaded purpose sentence followed by Args, Returns, and usage, which is easy to scan. It loses a bit of efficiency by duplicating the schema's parameter docs verbatim in the Args block.

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

Completeness5/5

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

With no output schema present, the description covers the return shape explicitly and lists the result fields, plus provides usage context and a follow-up tool. Nothing an agent needs to invoke and interpret results correctly is missing.

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% and every parameter is fully documented there, including defaults, clamping, and enum-like value lists. The description's Args block largely restates the schema, adding only example query strings, so the baseline 3 applies.

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

Purpose5/5

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

States a specific verb and resource ("Search the catalog of 3500+ MCP servers") and scopes it to servers, which cleanly separates it from siblings like search_ai_tools, search_mcp_tutorials, and get_mcp_details.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit trigger phrasing ("find me an MCP for X", "what MCP servers work with Cursor", "Slack MCP servers") and names the follow-up tool get_mcp_install_config for the next step, so the agent knows both when to enter and where to go after.

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

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