ToolFront

Organization

kruskal-labs

Search for the agentic web.

Publisher	kruskal-labs
Repository	`toolfront`
Language	TypeScript
Forks	67
Stars	876
Available tools	0
Transport type	stdio
Categories	Databases AI Ml
License	MIT
Links	GitHub Homepage

Connect tools to AI workflows
ToolFront exposes MCP capabilities that can be used by compatible AI clients and agents.
0 available tools
Browse the callable actions below, including names and descriptions when provided by the server.
Ready-to-copy setup
Use the installation snippets to configure this server in your preferred MCP client.
Open source signals
876 stars and 67 forks from the linked repository.

Website: https://statespace.com

Search Markdown and .txt pages from llms.txt sites. Available as a CLI, SDK, MCP server, and agent skill.

Installation

bash
npm install @statespace-tech/statespace

Query syntax

Plain queries search across all sites:


mcp server setup
vector database embeddings
rate limiting middleware
oauth2 token refresh
websocket reconnection strategy

Scope a query to a specific site with site: query:


stripe: webhook verification
supabase: edge functions auth
vercel: edge middleware caching
mistral.ai: function calling               # match by domain
docs.aws.amazon.com: s3 presigned urls     # match by subdomain

Use quotes for exact phrase matching:


"context window limit"
vector database "semantic search"
stripe: "webhook signature verification"

CLI

Search documentation from the command line: npx @statespace-tech/statespace search <query> [options]

bash
npx @statespace-tech/statespace search "mcp server setup"
npx @statespace-tech/statespace search "stripe: webhook verification" --limit 5
npx @statespace-tech/statespace search "redis connection pooling" --limit 10 --offset 3
npx @statespace-tech/statespace search "anthropic: tool function calling" --limit 5 --human

Flag	Short	Default	Max	Description
`--limit <n>`	`-l`	`10`	`50`	Max results to return
`--offset <n>`	`-o`	`0`	—	Results to skip (for pagination)
`--human`	—	—	—	Human-readable output instead of JSON

SDK

Import and call search() directly from TypeScript or JavaScript.

typescript
import { search } from '@statespace-tech/statespace';

const results = await search("mcp server setup");
const results = await search("stripe: webhook verification", { limit: 5 });
const results = await search("redis connection pooling", { limit: 10, offset: 3 });

MCP

Add to your MCP config to expose a search tool to your agents:

json
{
  "mcpServers": {
    "statespace": {
      "command": "npx",
      "args": ["@statespace-tech/statespace", "mcp"]
    }
  }
}

Agent skill

See SKILL.md

Requirements

Node.js 18+

Community & Contributing

Discord: Join our community server for real-time help and discussions
X: Follow us @statespace_tech for updates and news
Issues: Report bugs or request features on GitHub Issues

License

MIT

Installation

TypingMind

Prerequisites:

Node.js 18+

{
  "mcpServers": {
    "toolfront": {
      "command": "uvx",
      "args": [
        "toolfront[snowflake]",
        "snowflake://user:pass@account/warehouse/database"
      ]
    }
  }
}

Use ToolFront MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once ToolFront is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

Open TypingMind in your browser.
Click the Settings icon.
Go to Advanced Settings.
Open the Model Context Protocol section.
Click Setup Connector and choose This Device.

TypingMind MCP connector setup screen with This Device selected

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

Copy the setup command shown by TypingMind.
Open Terminal on macOS or Windows Terminal on Windows.
Paste and run the command.
Approve the package install if Terminal asks you to proceed.
Keep the Terminal window running while using MCP tools.

Add ToolFront as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

Wait until the connector status shows Ready.
Click Edit Servers.
Paste the ToolFront MCP server configuration.
Save the server list.
Refresh if you want to confirm the connector is still ready.

TypingMind MCP settings showing active server and Edit Servers button

Use it across models

Save the server list, open Plugins, enable the ToolFront MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

Open the Plugins page in TypingMind.
Enable the ToolFront MCP tools.
Start a chat and choose the AI model you want to use.
Use the MCP tools in chat or assign them to an AI agent.
Switch to another AI model whenever needed without reconnecting MCP.

TypingMind chat using enabled MCP tools with a selected AI model

Frequently asked questions

What is the ToolFront MCP server used for?

ToolFront is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use ToolFront MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use ToolFront with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use ToolFront MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With ToolFront connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect ToolFront MCP to TypingMind?

ToolFront runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does ToolFront MCP provide in TypingMind?

ToolFront exposes MCP capabilities that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use ToolFront MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If ToolFront requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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Installation

Query syntax

CLI

SDK

MCP

Agent skill

Requirements

Community & Contributing

License

Installation

Use ToolFront MCP with multiple AI models

Setup guide to use the local connector

Open the MCP settings

Run the connector command

Add ToolFront as a server

Use it across models

Frequently asked questions

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