About Parallel Search
Parallel Search MCP is a hosted remote MCP server from Parallel that gives coding agents real-time web search and page content extraction. Basic use needs no account or API key, and it suits users who need to check documentation and facts.
Key features
- 01web_search returns excerpts with source links
- 02web_fetch reads content from specified URLs
- 03Anonymous access with no account or API key
- 04Setup guides for Codex, Gemini CLI, OpenCode and Cursor
- 05Authenticated connections allow search behavior settings
Use cases
- 01Ask a coding agent to find official docs with sources
- 02Check the latest stable release and its notes
- 03Read a specified web page and explain its content
MCP support
This project is a remote MCP server reached over Streamable HTTP at https://search.parallel.ai/mcp, exposing web_search and web_fetch tools to MCP clients.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://search-mcp.parallel.ai/mcpclaude mcp add --transport http parallel https://search-mcp.parallel.ai/mcp{"mcpServers":{"parallel":{"type":"http","url":"https://search-mcp.parallel.ai/mcp"}}}Open in Cursor{"servers":{"parallel":{"type":"http","url":"https://search-mcp.parallel.ai/mcp"}}}Open in VS Code{"mcpServers":{"parallel":{"type":"http","url":"https://search-mcp.parallel.ai/mcp"}}}{"mcpServers":{"parallel":{"serverUrl":"https://search-mcp.parallel.ai/mcp"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
Tools
2| Parameter | Type | Required | Description |
|---|---|---|---|
| objective | string | Yes | Natural-language description of what the web search is trying to find. Try to make the search objective atomic, looking for a specific piece of information. May include guidance about preferred sources or freshness. |
| search_queries | array | Yes | Concise keyword search queries, 3-6 words each, which may include search operators. At least one query is required; provide 2-3 for best results. For broad tasks, you can include multiple related queries in a single call instead of chaining web_search calls. The queries should be related to the objective. |
| session_id | string | No | Stable identifier for the current conversation. Generate a random value (UUID or 32+ character hex string) at the start of your session and reuse the exact same value on every web_search / web_fetch call. Do NOT change it between turns. Used for free-tier rate limiting and correlating your tool calls in our logs; ignored on paid-tier keys. |
| model_name | string | No | The identifier of the LLM model making this tool call (e.g. 'claude-opus-4.7', 'gpt-5.5', 'gemini-2.5-pro'). Before the first call, verify the exact active model slug from trusted runtime/session metadata or active client configuration. Pass the full slug verbatim; never shorten or substitute a model-family alias like 'gpt-5'. Used for product analytics only; does not affect search behavior. |
Details
From the project READMEParallel Search MCP
Free web search for your coding agent.
Find current documentation, check facts, and read web pages without leaving your agent. No account or API key needed to get started.
Ask your agent to install
Copy this into your coding agent:
Install Parallel's free Search MCP in the coding agent I'm using now.
Identify your client and use its native MCP setup instructions:
https://docs.parallel.ai/integrations/mcp/search-mcp
Server name: parallel-search
Server URL: https://search.parallel.ai/mcp
Transport: Streamable HTTP
Authentication: none. No account, API key, or Parallel CLI is needed.
Preserve existing settings and reuse any connection to this endpoint.
Tell me if a restart or approval is required.
Once connected, check that web_search and web_fetch are available.
Use Parallel to find the official FastAPI response-model documentation
and return a source link. Report anything you couldn't verify.
Install in Cursor · Install in VS Code · Manual setup · Documentation
Manual setup
Choose your client. You only need one of these options.
Codex
codex mcp add parallel-search --url https://search.parallel.ai/mcp
Start a new Codex session and run /mcp to check the connection. See the Codex MCP guide for configuration options.
Gemini CLI
gemini extensions install https://github.com/parallel-web/search-mcp
Restart Gemini CLI and run /mcp to check that parallel-search is connected. The extension uses Streamable HTTP and requires no Parallel account or API key. If you already configured parallel-search manually, that configuration takes precedence over the extension. See the extension guide for installation and update options.
Hermes Agent
Hermes already includes Parallel in its native web providers. Choose Parallel Free (keyless) in hermes tools to use that integration.
This optional package adds a direct connection to Parallel's MCP tools and the bundled setup skill. It leaves Hermes's native web-provider selection unchanged. It's available in the Hermes plugin catalog. Install and enable it with:
hermes plugins install parallel-search
hermes plugins enable parallel-search
Start a new session so Hermes loads the enabled package. Ask Hermes to use the Parallel MCP web_search tool to find official documentation, then web_fetch to read a page. Use skills_list to discover the namespaced parallel-search-setup skill. No Parallel account, API key, or CLI is required.
Use either this package or a manually configured connection to https://search.parallel.ai/mcp to avoid duplicate MCP tools. Disable or remove the package with hermes plugins disable parallel-search or hermes plugins remove parallel-search. Update through hermes plugins update parallel-search; catalog updates use reviewed commit pins.
OpenCode
Merge this into your project's opencode.json:
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"parallel-search": {
"type": "remote",
"url": "https://search.parallel.ai/mcp",
"oauth": false
}
}
}
Restart OpenCode and run opencode mcp list to check the connection. See the OpenCode MCP guide for details.
OpenClaw
Follow the OpenClaw setup guide to install the Parallel plugin, then set tools.web.search.provider to parallel-free. No Parallel account or API key is needed.
Cursor, VS Code, and other clients
Use this remote MCP server URL:
https://search.parallel.ai/mcp
Select HTTP or Streamable HTTP if your client asks for a transport. Follow the client-specific instructions for the right settings file and format.
Try it
Ask your agent:
Use Parallel to find the official FastAPI docs for response models. Show me a small example and link to the source.
Or try:
Use Parallel to check the latest stable Node.js release and its release notes. Cite the official sources.
Use Parallel to read https://modelcontextprotocol.io/introduction and explain how MCP connects an agent to tools.
Your agent can use two tools:
| Tool | What it does |
|---|---|
web_search | Searches the web and returns relevant excerpts with source links. |
web_fetch | Reads specific URLs and returns page content for your agent to use. |
Search results often contain enough information to answer. Your agent can fetch a page when it needs more detail.
Free access and higher limits
This plugin is anonymous by design: both tools work with no account, API key, or login, subject to free-tier rate limits. The free tier is intended for personal agents, hobby projects, and exploration.
For higher limits, usage analytics, and production workloads, create an account at platform.parallel.ai and connect the Parallel Search connector, which signs in with that account. Authenticated usage is billed under your account's pricing and limits — see parallel.ai for pricing. Don't add an API key or point this plugin at an authenticated endpoint; the connector handles sign-in natively.
Both tiers include the same two tools. Authenticated connections also let you configure search behavior, including search modes, result counts, and domain filters. Anonymous requests ignore these settings.
Privacy and terms
Parallel hosts the service. Search queries and requested URLs are sent to Parallel and handled under the Customer Terms and Privacy Policy. The server only receives what the tools send it — search queries and the URLs you ask it to fetch — and does not read your conversation, files, or other context.
Troubleshooting
- Tools aren't showing up: start a new agent session and check its MCP connection list. Confirm the URL is
https://search.parallel.ai/mcp. - Asked to log in to Parallel: check the URL.
/mcpsupports free access;/mcp-oauthrequires authentication. Approving an MCP connection in your client is separate from logging in to Parallel. - Hit a rate limit: wait before retrying, or move to an authenticated Parallel account via the Parallel Search connector for higher limits.
- Still stuck: check the setup guide or open an issue. Include your client, version, and error message. Leave out API keys and other credentials.
Support and security
- Questions and bugs: open an issue with your client, version, and error message (leave out API keys and other credentials), or see the documentation.
- Product support: contact Parallel at [email protected].
- Security concerns: report privately to [email protected] — see SECURITY.md. Please don't file security reports as public issues.
About this repo
This is the official GitHub home for Parallel's hosted Search MCP. It contains this guide and Codex, Cursor, Gemini CLI, and Hermes packages. Codex and Cursor share .mcp.json; Hermes uses the portable Agent Plugins v1 plugin.json and mcp.json files and loads the setup skill (skills/parallel-search-setup/SKILL.md) on demand for connection checks, usage guidance, troubleshooting, and higher-limit options. You can suggest documentation fixes and examples here. The search service runs on Parallel's infrastructure; cloning this repo gives you the documentation and configuration files.
For CLI-based search, research, and enrichment, see the separate Parallel CLI skills plugin.
The files in this repo are MIT licensed. Hosted service usage is covered by the Customer Terms linked above.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.