Orcha
About
Orcha is a unified context layer for AI tools and agents. It stores and indexes and exposes organizational, team, or individual knowledge. Files, structured databases, and connected sources live in one workspace, and age
Details
- Author
- westonhancock
- Downloads
- 1,190
- Categories
- Knowledge Base
Jump to
- File and folder reading, creation, update, organization, and deletion, scoped to what the connection is allowed to touch
- Curated context bundles with usage guidance (list_bundles, get_bundle)
- Structured databases with typed queries (list_databases, query_database, record CRUD)
- Direct access to connected read-only sources (query_source, fetch_source_document, list_source_documents)
- Filesystem-shaped browsing (browse_context): ls, tree, find, cat, grep, and stat over a virtual tree of the workspace
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
OrchaCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Follow the repository README to install the server and add its MCP configuration to your client.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"orcha": {
"orcha": {
"type": "streamable-http",
"url": "https://app.tryorcha.com/mcp"
}
}
}
}
McpServers
{
"orcha": {
"type": "streamable-http",
"url": "https://app.tryorcha.com/mcp"
}
}
Orcha is a unified context layer for AI tools and agents. It stores and indexes and exposes organizational, team, or individual knowledge. Files, structured databases, and connected sources live in one workspace, and agents reach them through Model Context Protocol (MCP), CLI with virtual file system, or REST API, with permissions, citations, and provenance.
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