Search Registry logo

Search Registry

Organization
agentic-community
search-registry

Search the MCP Gateway Registry using semantic search. Takes a natural language query, calls the /api/search/semantic endpoint, and returns formatted results directly in the conversation.

Overview

Publisheragentic-community
Repositorymcp-gateway-registry
Skill namesearch-registry
Stars
969
Forks
244
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by agentic-community on GitHub. Read the source before you install it.

Installation

Install the Search Registry AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/agentic-community/mcp-gateway-registry/tree/main/.claude/skills/search-registry
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/agentic-community/mcp-gateway-registry.git /tmp/mcp-gateway-registry
mkdir -p .claude/skills
cp -r /tmp/mcp-gateway-registry/.claude/skills/search-registry .claude/skills/search-registry
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Search Registry in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Search Registry on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Search Registry is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Search Registry Skill

Search the MCP Gateway Registry for MCP servers, tools, A2A agents, skills, and virtual servers using the ai-registry-tools MCP server.

Prerequisites

The user must have the AI Registry MCP server connected to their AI Assistant session. It may be registered under various names including:

  • ai-registry-tools
  • airegistry-tools
  • ai_registry_tools
  • registry-tools
  • mcp-registry

The key indicator is that one of these tools should be available:

  • mcp__ai-registry-tools__search_registry
  • mcp__airegistry-tools__search_registry
  • or similar variations

Input

The skill accepts a natural language search query:

/search-registry <query>
  • query - What capability, tool, server, or agent the user is looking for (natural language)

If no query is provided, ask the user: "What would you like to search for in the registry?"

Examples

/search-registry tools for weather data
/search-registry exchange rates currency conversion
/search-registry document processing PDF
/search-registry travel booking flights

Workflow

Step 1: Find the Registry Search Tool

Look for the search_registry tool from the ai-registry-tools MCP server. It may be available under different prefixes depending on how the user registered the server. Try these in order:

  1. mcp__ai-registry-tools__search_registry
  2. mcp__airegistry-tools__search_registry
  3. mcp__ai_registry_tools__search_registry
  4. mcp__registry-tools__search_registry
  5. mcp__mcp-registry__search_registry

Use ToolSearch to find the correct tool name if none of the above work. Search for "search_registry" or "registry search".

If the tool cannot be found, tell the user:

"The AI Registry MCP server is not connected to this AI Assistant session. You need to add it first. See the registry documentation for connection instructions specific to your AI Assistant (Claude Code, Codex CLI, etc.)."

Step 2: Execute the Search

Call the search_registry tool with:

  • query: the user's natural language query
  • max_results: 10

Step 3: Present Results

Display the results in this format:

### Registry Search Results

**Query:** {query}
**Found:** {count} servers, {count} tools, {count} agents, {count} skills

---

For each result category that has results, show a table:

MCP Servers
NamePathScoreToolsTransportEndpoint
{server_name}{path}{relevance_score}{num_tools}{supported_transports}{endpoint_url}

For servers with matching_tools, list them below:

{server_name} matching tools:

ToolDescription
{tool_name}{description truncated to 80 chars}
Tools
ToolServerScoreEndpointDescription
{tool_name}{server_name}{relevance_score}{endpoint_url}{description truncated to 80 chars}
A2A Agents
NamePathScoreURLDescription
{name}{path}{relevance_score}{url}{description truncated to 80 chars}
Skills
NamePathScoreDescription
{skill_name}{path}{relevance_score}{description truncated to 80 chars}

After the tables, provide a brief plain-text summary of the top 3-5 most relevant results.

Step 4: Offer to Add MCP Servers

IMPORTANT: After presenting results, if any MCP servers were found that have an endpoint_url, ask the user:

"Would you like to add any of these MCP servers to your AI Assistant configuration? If so, which one(s)?"

Present the available servers as options (only those with a valid endpoint_url).

Step 5: Add Server to AI Assistant

If the user says yes and picks a server, determine which AI Assistant is being used and add the server using the appropriate method for that assistant.

Detecting the AI Assistant

Check for configuration files to determine the assistant in use:

  1. Claude Code: Look for .mcp.json in the project root or ~/.claude/settings.json
  2. Codex CLI: Look for codex.json or .codex/ configuration directory
  3. Other assistants: Ask the user which assistant they are using if it cannot be determined automatically
Adding for Claude Code

Method 1 (preferred): Use the claude mcp add command

Run this command (either in a terminal or prefixed with ! inside a Claude Code session):

bash
claude mcp add --transport http --scope user <server-name> <endpoint_url>

For example:

bash
claude mcp add --transport http --scope user real-server-fake-tools https://mcpgateway.ddns.net/realserverfaketools/mcp

This saves the server to ~/.claude.json at user scope, making it available across all projects.

Method 2: Update ~/.claude.json directly

Add the new server to the mcpServers object in ~/.claude.json (the user-level config file where ai-registry-tools and other MCP Gateway servers are configured):

json
{
  "mcpServers": {
    "existing-server": { ... },
    "new-server-name": {
      "type": "http",
      "url": "<endpoint_url from the search result>"
    }
  }
}

Note: Do NOT add servers to the project-level .mcp.json file. That file is committed to git and should not contain user-specific MCP server configurations. Use ~/.claude.json (user scope) for servers that persist across projects.

Adding for Codex CLI

Update the Codex MCP configuration file (typically ~/.codex/mcp.json or the project-level equivalent):

json
{
  "servers": {
    "new-server-name": {
      "url": "<endpoint_url from the search result>"
    }
  }
}

Or use the Codex CLI command if available:

bash
codex mcp add <server-name> --url <endpoint_url>
Adding for Other Assistants

If the AI Assistant cannot be determined or is not one of the above, provide the user with the raw connection details and let them configure it manually:

"Here are the connection details for the server:

  • Name: {server_name}
  • Endpoint URL: {endpoint_url}
  • Transport: streamable-http

Add this to your AI Assistant's MCP server configuration using the method appropriate for your tool."

Server Name Convention

Claude Code only allows server names containing letters, numbers, hyphens, and underscores. Dots and slashes are not allowed.

To derive a valid server name from the server's path field:

  1. Remove the leading slash
  2. Replace slashes with hyphens
  3. Remove dots or replace them with hyphens
  4. If the result is still unclear, use the server_name field as inspiration for a short, descriptive name

Examples:

  • Path /ai.agenticshelf-graffeo with server_name "ai.agenticshelf/graffeo" (a coffee catalog) becomes graffeo-coffee
  • Path /realserverfaketools/ becomes real-server-fake-tools
  • Path /ai.com.mcp-openai-tools becomes openai-tools

Step 6: Inform User About New Session

After successfully adding the server, tell the user:

"Server '{server_name}' has been added to your AI Assistant's MCP configuration.

You will need to start a new session to use this server's tools. I cannot start the new session for you, but you can continue this conversation in that session. The new tools from '{server_name}' will be available once you restart."

Fallback: Browse the Full Catalog

If the semantic search returns no relevant results (or the user is unsure what to search for), fall back to listing the full catalog using these tools:

  • list_services - Lists all registered MCP servers (unfiltered). Good for browsing what is available.
  • list_agents - Lists all registered A2A agents.
  • list_skills - Lists all registered skills.

Tell the user:

"The semantic search did not find a close match. Let me list the full catalog so you can browse what is available."

Then call the appropriate listing tool(s) and present the results in a similar table format. If the user finds something of interest from the listing, continue with Step 4 (offer to add it).

Additionally, if a skill is found that looks useful, offer to fetch its full instructions using get_skill_content with the skill name.

Available Registry Tools Reference

The ai-registry-tools MCP server provides these tools:

ToolPurpose
search_registrySemantic search across all entity types (primary search tool)
list_servicesList all MCP servers in the registry (unfiltered)
list_agentsList all A2A agents in the registry (unfiltered)
list_skillsList all skills in the registry (unfiltered)
get_skill_contentFetch full SKILL.md instructions for a skill by name
healthcheckCheck registry health status and statistics

Error Handling

  • Tool not found: Tell the user the ai-registry-tools MCP server is not connected and how to add it.
  • No results from search: Tell the user no results were found, then offer to list the full catalog using list_services, list_agents, or list_skills so they can browse what is available.
  • Search error: Display the error message from the tool response and suggest the user check their registry connection.
  • Server already exists in config: If the user picks a server that's already in their MCP configuration, tell them it's already configured.

Notes

  • Always search ALL entity types. Do not ask the user to filter by category.
  • The endpoint_url field on servers is the streamable-http MCP endpoint that can be added directly to any AI Assistant that supports MCP.
  • Some servers may have authentication requirements. If the endpoint requires auth headers, note this to the user when offering to add the server. They may need to add headers manually to the config after.
  • Do NOT add servers without user confirmation. Always ask first.

Frequently asked questions

What does the Search Registry AI skill do?

Search the MCP Gateway Registry using semantic search. Takes a natural language query, calls the /api/search/semantic endpoint, and returns formatted results directly in the conversation.

Why use Search Registry on TypingMind?

Because you install it once and use it with any model. Search Registry is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Search Registry in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/agentic-community/mcp-gateway-registry/tree/main/.claude/skills/search-registry. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Search Registry?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Search Registry?

As many as you like. As long as a model supports skills, you can use Search Registry with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Search Registry AI skill free?

Yes. It is published on GitHub by agentic-community under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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