LLM-ready web search + instant answers + URL-to-clean-text fetch for agents and RAG.
LLM-ready web search + instant answers + URL-to-clean-text fetch for agents and RAG. Exposed over MCP by the agentsearch mcp server, that capability becomes something an assistant can invoke while it works, not something you go and do afterwards.
A remote MCP (Model Context Protocol) connector for AgentSearch API — an LLM/MCP-native web toolkit for agents and RAG pipelines: web search (provider-abstracted SERP), keyless instant answers, and URL → clean text/markdown fetch ready for an LLM context window.
Being a remote server, there is no local install. You register the endpoint with your client, authorise it once, and the tools appear.
You will need 2 environment variables: AGENTSEARCH_MCP_PROXY_SECRET, AGENTSEARCH_MCP_API_BASE_URL. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.
This sits in the AI and media services group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. It is maintained by IsaiahDupree; worth a glance at recent repository activity before you build anything load-bearing on it.
We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.
{
"mcpServers": {
"agentsearch": {
"command": "npx",
"args": ["-y", "npm"],
"env": {
"AGENTSEARCH_MCP_PROXY_SECRET": "your-value",
"AGENTSEARCH_MCP_API_BASE_URL": "your-value"
}
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
| Variable | Description | Required |
|---|---|---|
| AGENTSEARCH_MCP_PROXY_SECRET | Credential the server authenticates with. | Yes |
| AGENTSEARCH_MCP_API_BASE_URL | Endpoint or connection string the server talks to. | Yes |
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.
Answers, not links — delegate questions to Perplexity's search-grounded models and get cited responses back.
Give your assistant a voice — text-to-speech, voice cloning and audio tools from the ElevenLabs API.
Give your assistant a real code sandbox — isolated cloud VMs for actually running the code it writes.
The ML hub in your context window — search models, datasets, papers and run Spaces from the official server.