Skip to main content
Glama
hifriendbot

ailist-mcp

by hifriendbot

search_projects

Search and browse a curated directory of AI projects including MCP servers, CLI tools, libraries, and APIs. Filter by category, sort by stars or trending, and refine by technology.

Instructions

Search and browse Ai projects on AiList. Find MCP servers, CLI tools, libraries, web apps, APIs, plugins, models, datasets, and agents. Supports filtering by category and sorting by stars, trending, newest, name, or views.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number (default 1)
sortNoSort order: stars (default), trending, newest, name, viewsstars
queryNoSearch query (optional — omit to browse all projects)
categoryNoFilter by category: mcp-server, cli-tool, library, web-app, api, plugin, model, dataset, agent, other
per_pageNoResults per page (default 24, max 100)
built_withNoFilter by technology used (e.g. "Claude Code", "Cursor")

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.4

TDQS

A3.7/5.0
Behavior3/5

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

No annotations are provided, so the description carries full burden. It describes the operation (search and browse) but does not disclose whether it is read-only, any side effects, rate limits, or pagination behavior. It is adequate for a search tool but lacks depth expected without annotations.

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 sentences, front-loaded with the core purpose, and every sentence adds value. No redundancy or fluff. It is appropriately concise for the tool's complexity.

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?

Given 6 parameters, no output schema, and no annotations, the description covers the main search and browse functionality but omits details like pagination behavior, default sort, or what the response format looks like. It is complete enough for basic use but could be more informative for an agent.

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 baseline is 3. The description adds context by listing project types (MCP servers, CLI tools, etc.) and mentions filtering/sorting, but it largely echoes the schema. It does not add substantial meaning beyond what the schema already provides for each parameter.

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?

The description clearly states the tool searches and browses AI projects on AiList, specifying it finds MCP servers, CLI tools, libraries, etc. It mentions filtering by category and sorting options, which clearly distinguishes it from siblings like get_trending (likely just trending) or get_project (single project).

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

Usage Guidelines3/5

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

The description implies when to use the tool (for general search and browse) but does not explicitly differentiate from siblings or state when not to use it. For example, it could mention that get_trending is for trending-only or get_project for a specific project. The guidance is implied but not explicit.

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

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/hifriendbot/ailist-mcp'

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