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MemContext provides a hosted MCP server — no local installation required. Add the connection URL and your API key to your client, then add the recommended agent instructions for the best experience.

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Prerequisites

  • A MemContext account at app.memcontext.in
  • An API key (create one under Settings > API Keys)
The MCP page in your dashboard generates ready-to-paste configs with your API key pre-filled.

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Claude Code

Step 1 — Add the MCP server via CLI: 
claude mcp add memcontext --scope user --transport http https://mcp.memcontext.in/mcp \
  --header "MEMCONTEXT-API-KEY:mc_your_key"
Or add this to ~/.claude.json: 
{
  "mcpServers": {
    "memcontext": {
      "url": "https://mcp.memcontext.in/mcp",
      "headers": {
        "MEMCONTEXT-API-KEY": "mc_your_key"
      }
    }
  }
}
Step 2 — Add agent instructions to ~/.claude/CLAUDE.md: 
# MemContext

At conversation start, ALWAYS call search_memory to load user context — do not skip.
Before making decisions or assumptions, search_memory to check for past context.
SAVE immediately (do not defer) when any of these happen:

- User shares a preference → save_memory(category: "preference")
- A technology or architecture decision is made → save_memory(category: "decision")
- User corrects you or says "remember" → save_memory(category: "fact")
- Important project fact learned → save_memory(category: "fact", project: "<name>")
- Significant work completed → save_memory(category: "context")
  For time-sensitive info, use validUntil: save_memory(content: "...", validUntil: "2026-05-01T00:00:00Z")
  After using search results, call memory_feedback to rate memories as helpful/not_helpful/outdated.
  Use delete_memory only when a memory was saved incorrectly and should be removed entirely.
  Duplicates are handled automatically — when in doubt, save.
  Memory persists across all sessions - use project param for project-specific context only.

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Cursor

Step 1 — Add this to ~/.cursor/mcp.json: 
{
  "mcpServers": {
    "memcontext": {
      "url": "https://mcp.memcontext.in/mcp",
      "headers": {
        "x-api-key": "mc_your_key"
      }
    }
  }
}
Step 2 — Add the agent instructions to Cursor Settings > Rules and commands > User Rules.

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OpenCode

Step 1 — Add the MCP server to ~/.config/opencode/opencode.json: 
{
  "mcp": {
    "memcontext": {
      "type": "local",
      "command": [
        "npx",
        "-y",
        "mcp-remote",
        "https://mcp.memcontext.in/mcp",
        "--header",
        "MEMCONTEXT-API-KEY:mc_your_key"
      ],
      "enabled": true
    }
  }
}
Step 2 — Add the agent instructions to ~/.config/opencode/AGENTS.md.

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Codex CLI

Step 1 — Add the MCP server to ~/.codex/config.toml: 
[mcp_servers.memcontext]
url = "https://mcp.memcontext.in/mcp"

[mcp_servers.memcontext.http_headers]
MEMCONTEXT-API-KEY = "mc_your_key"
Step 2 — Add the agent instructions to ~/.codex/instructions.md.

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Agent instructions

These instructions tell your AI assistant how and when to use MemContext. Add them to the preferences file for your client (listed above): 
# MemContext

At conversation start, ALWAYS call search_memory to load user context — do not skip.
Before making decisions or assumptions, search_memory to check for past context.
SAVE immediately (do not defer) when any of these happen:

- User shares a preference → save_memory(category: "preference")
- A technology or architecture decision is made → save_memory(category: "decision")
- User corrects you or says "remember" → save_memory(category: "fact")
- Important project fact learned → save_memory(category: "fact", project: "<name>")
- Significant work completed → save_memory(category: "context")
  For time-sensitive info, use validUntil: save_memory(content: "...", validUntil: "2026-05-01T00:00:00Z")
  After using search results, call memory_feedback to rate memories as helpful/not_helpful/outdated.
  Use delete_memory only when a memory was saved incorrectly and should be removed entirely.
  Duplicates are handled automatically — when in doubt, save.
  Memory persists across all sessions - use project param for project-specific context only.
ClientPreferences file
Claude Code~/.claude/CLAUDE.md
CursorCursor Settings > Rules and commands > User Rules
OpenCode~/.config/opencode/AGENTS.md
Codex CLI~/.codex/instructions.md

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Available tools

Once connected, your assistant has access to four tools:
ToolPurpose
save_memoryPersist preferences, facts, decisions, and context
search_memoryFind relevant memories before responding
memory_feedbackRate memory quality after retrieval
delete_memoryRemove a memory by ID
See the MCP Tools section for parameter documentation.

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Verifying the connection

After setup, ask your assistant:
“Search your memory for any information about me.”
If the connection is working, it will call search_memory and return results (or an empty set if no memories exist yet).