Context Link

Official4 tools

by context-link

One semantic search across your sites, Drive, Notion, email, files and Basecamp.

ai.context-link/context-link MCP Server

The ai.context-link/context-link MCP server provides “one semantic search” across multiple sources, including websites, Drive, Notion, email, files, and Basecamp. Its scope is cross-source retrieval using a single search experience, based on the server description provided.

🛠️ Key Features

One semantic search across your sites
Supports searching: Drive, Notion, email, files, Basecamp

🚀 Use Cases

Find relevant information across websites and productivity/work platforms
Search content stored in Drive, Notion, and Basecamp alongside emails and files

⚡ Developer Benefits

Single search entry point spanning multiple data sources

⚠️ Limitations

Only the cross-source semantic search behavior is described; no additional tools, authentication, or indexing details are provided

Captured live from the server via tools/list.

get_context

Get context from the user's connected workspaces and websites. The attached widget displays only the list of sources consulted — it does not show the retrieved content, so use the returned context to answer the user directly.

Parameters3

query	string	required
mode	string	optional	Optional mode to weight results (e.g. 'customer-support')
connection_type	string	optional	Optional comma-separated list of connection types to restrict retrieval to (e.g. "site,email"). Only content from those sources is considered. Valid types: basecamp, custom, email, files, google_doc, memory, monday, notion, one_drive, site, webmention, youtube.

Raw schema

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string"
    },
    "mode": {
      "type": "string",
      "description": "Optional mode to weight results (e.g. 'customer-support')"
    },
    "connection_type": {
      "type": "string",
      "description": "Optional comma-separated list of connection types to restrict retrieval to (e.g. \"site,email\"). Only content from those sources is considered. Valid types: basecamp, custom, email, files, google_doc, memory, monday, notion, one_drive, site, webmention, youtube."
    }
  },
  "required": [
    "query"
  ],
  "$schema": "https://json-schema.org/draft/2020-12/schema"
}

ask_question

Ask a question about the user's connected workspaces and websites and receive a concise answer with citations. The attached widget displays only the list of sources consulted — it does not show the answer, so always relay the answer text in your reply.

Parameters3

query	string	required
mode	string	optional	Optional mode to weight results (e.g. 'customer-support')
connection_type	string	optional	Optional comma-separated list of connection types to restrict retrieval to (e.g. "site,email"). Only content from those sources is considered. Valid types: basecamp, custom, email, files, google_doc, memory, monday, notion, one_drive, site, webmention, youtube.

Raw schema

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string"
    },
    "mode": {
      "type": "string",
      "description": "Optional mode to weight results (e.g. 'customer-support')"
    },
    "connection_type": {
      "type": "string",
      "description": "Optional comma-separated list of connection types to restrict retrieval to (e.g. \"site,email\"). Only content from those sources is considered. Valid types: basecamp, custom, email, files, google_doc, memory, monday, notion, one_drive, site, webmention, youtube."
    }
  },
  "required": [
    "query"
  ],
  "$schema": "https://json-schema.org/draft/2020-12/schema"
}

save_memory

Save content to the user's memory for later retrieval. Use this when the user wants to save information, notes, or conversation content.

Parameters2

content	string	required	The content to save. Can be plain text, markdown, or structured content.
namespace	string	optional	A name/label for this memory (use-dashes-for-spaces). If omitted, a timestamped name is generated.

Raw schema

{
  "type": "object",
  "properties": {
    "content": {
      "type": "string",
      "description": "The content to save. Can be plain text, markdown, or structured content."
    },
    "namespace": {
      "type": "string",
      "description": "A name/label for this memory (use-dashes-for-spaces). If omitted, a timestamped name is generated."
    }
  },
  "required": [
    "content"
  ],
  "$schema": "https://json-schema.org/draft/2020-12/schema"
}

get_memory

Retrieve previously saved memory content by its namespace. Use this when the user wants to recall saved content.

Parameters1

namespace

string

required

The namespace/name of the saved memory to retrieve

Raw schema

{
  "type": "object",
  "properties": {
    "namespace": {
      "type": "string",
      "description": "The namespace/name of the saved memory to retrieve"
    }
  },
  "required": [
    "namespace"
  ],
  "$schema": "https://json-schema.org/draft/2020-12/schema"
}

Install

Tools (4)

get_contextask_questionsave_memoryget_memory

Remote endpoint

Streamable HTTP

Hosted server - connect over the network, no local install.

url

https://www.context-link.ai/mcp

Add to VS Code Add to Cursor

claude_desktop_config.json

json

{
  "mcpServers": {
    "context-link": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://www.context-link.ai/mcp"
      ]
    }
  }
}

Desktop config is stdio-only; this bridges via mcp-remote. Native remote: Settings > Connectors.

ai.context-link/context-link MCP Server

🛠️ Key Features

🚀 Use Cases

⚡ Developer Benefits

⚠️ Limitations

get_context

ask_question

save_memory

get_memory

Install

Remote endpoint

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