IDEs & Agents — MCP Server

Memwyre provides a fully compliant Model Context Protocol (MCP) server. This lets your local AI agents, code editors, and desktop apps seamlessly read from and write to your Memwyre vault.

Overview

The Model Context Protocol is an open standard that connects AI systems with external tools and data sources. By running the Memwyre MCP Server locally, you give your IDE or agent (Claude Desktop, Cursor, VS Code, etc.) direct access to your centralised memory — no more copy-pasting context manually.

Prerequisites

Before you begin, make sure you have:

• Python 3.10+ installed on your machine.
• Your MEMWYRE_API_KEY — generate one from Settings → API Keys in the Memwyre web app.
• The mcp_server.py script downloaded to a permanent location on your hard drive.

Setup

Step 1 — Download the Server Script

Download mcp_server.py from your Memwyre dashboard and save it somewhere stable (e.g. ~/memwyre/mcp_server.py).

Step 2 — Configure Claude Desktop

Add the following block to your Claude Desktop config file:

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "memwyre": {
      "command": "python",
      "args": ["/absolute/path/to/mcp_server.py"],
      "env": {
        "MEMWYRE_API_KEY": "your_api_key_here"
      }
    }
  }
}

Replace /absolute/path/to/mcp_server.py with the actual path where you saved the file.

Step 3 — Configure VS Code or Cursor

In your IDE's MCP client settings, add a new server entry pointing to the script:

python /absolute/path/to/mcp_server.py

Set MEMWYRE_API_KEY in the environment variables section of your IDE's MCP configuration panel.

Available Tools

Once connected, your IDE or agent will have access to the following tools. Click on a tool to see its details and parameters:

search_memwyre (Primary Search)

The most important tool for retrieving context. It performs a semantic vector search across your entire vault.

• Parameters:
  • query (Required): Your search terms or question.
  • purpose (Optional): Hint for formatting results. Options: general, code, or summary.

save_memory (Capture Context)

Save new information or notes directly into your Memwyre Inbox.

• Parameters:
  • text (Required): The content you want to save.
  • tags (Optional): A list of tags to categorize the memory (e.g. ["project-x", "todo"]).
  • source (Optional): Origin of the memory (defaults to mcp).

generate_prompt (Prompt Engineering)

Retrieves relevant context and wraps it in a pre-formatted prompt for an LLM.

• Parameters:
  • query (Required): The topic to generate a prompt for.
  • template (Optional): The prompt structure. Options: standard, code, or summary.

get_document (Full Text Retrieval)

Retrieve the entire content of a specific document (PDF, Doc, or Web Page) by its ID.

• Parameters:
  • doc_id (Required): The numeric ID of the document (e.g. 123).

list_memories (Discovery)

List the most recent memories and documents added to your vault.

• Parameters:
  • limit (Optional): Number of items to return (default: 10).
  • offset (Optional): Pagination offset.

get_inbox (Pending Review)

Lists all memories currently in your "Inbox" status that are awaiting review or confirmation.

update_memory (Edit)

Update the content of an existing memory snippet.

• Parameters:
  • memory_id (Required): The ID of the memory, starting with mem_ (e.g. mem_45).
  • content (Required): The new text content.

delete_memory (Cleanup)

Permanently remove a memory or document from your vault.

• Parameters:
  • memory_id (Required): The ID of the item, starting with mem_ or doc_ (e.g. doc_12).

search_by_date (Chronological Search)

Find memories created within a specific timeframe.

• Parameters:
  • start_date (Required): Start date in YYYY-MM-DD format.
  • end_date (Optional): End date in YYYY-MM-DD format.

get_all_tags (Taxonomy)

Retrieve a comprehensive list of all tags currently used across your entire memory vault.

Troubleshooting

Claude Desktop doesn't show the Memwyre tools.
Check that the command path resolves correctly — try python3 instead of python on macOS/Linux.

MEMWYRE_API_KEY environment variable not found.
Make sure the key is set inside the env block of your config file, not as a system environment variable.