A
license-
qualityD
maintenanceEnables iterative deep research by integrating AI agents with search engines, web scraping, and large language models for efficient data gathering and comprehensive reporting.
Last updated
19
324
MIT
Parallel Task MCP
by parallel-web
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Parallel Task MCPresearch the latest developments in quantum computing"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Parallel Task MCP
The Parallel Task MCP allows initiating deep research or task groups directly from your favorite LLM client. It can be a great way to get to know Parallel’s different APIs by exploring their capabilities, but can also be used as a way to easily do small experiments while developing production systems using Parallel APIs. Please read our MCP docs here for more details.
Installation
The official installation instructions can be found here.
{
"mcpServers": {
"Parallel Task MCP": {
"url": "https://task-mcp.parallel.ai/mcp"
}
}
}Related MCP server: olostep-mcp
Running locally
This repo contains a proxy to the mcp which is hosted at: https://task-mcp.parallel.ai/mcp
How to run and test locally:
wrangler devnpx @modelcontextprotocol/inspectorConnect to server: http://localhost:8787/mcp
This server cannot be installed
Maintenance
–Maintainers
–Response time
–Release cycle
–Releases (12mo)
Commit activity
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
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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/parallel-web/task-mcp'
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