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Add MCP setup docs for Claude Code, Cursor, Codex, Windsurf
Complete setup guide with exact config format for each tool, PATH troubleshooting, Windows-specific notes, verification steps, all 13 tools documented, and usage tips. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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docs/index.html

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<a href="https://github.com/Thezenmonster/agentmem">GitHub</a> &middot;
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<a href="https://pypi.org/project/quilmem/">PyPI</a> &middot;
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<a href="quickstart.html">Quickstart</a> &middot;
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<a href="mcp-setup.html">MCP Setup</a> &middot;
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MIT License
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</p>
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<p style="margin-top:8px;">Built by <a href="https://github.com/Thezenmonster">Michael K Onyekwere</a></p>

docs/mcp-setup.md

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# MCP Setup Guide
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Connect agentmem to your coding agent in 2 minutes. Pick your tool.
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## Prerequisites
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```bash
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pip install quilmem[mcp]
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```
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Verify it works:
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```bash
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agentmem --help
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```
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If that prints the command list, you're good.
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---
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## Claude Code
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Claude Code reads MCP config from `~/.claude/settings.json` (global) or `.claude/settings.json` (project-level).
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### Option A: CLI (fastest)
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```bash
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claude mcp add agentmem -- agentmem --db ./memory.db --project myproject serve
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```
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That's it. Restart Claude Code. The 13 agentmem tools should appear.
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### Option B: Manual config
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Add this to `~/.claude/settings.json` (global) or `.claude/settings.json` in your project root:
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```json
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{
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"mcpServers": {
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"agentmem": {
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"command": "agentmem",
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"args": ["--db", "./memory.db", "--project", "myproject", "serve"],
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"type": "stdio"
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}
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}
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}
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```
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Replace `./memory.db` with wherever you want the database. Replace `myproject` with your project name (used for scoping if you run multiple projects on one DB).
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### If agentmem isn't on PATH
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Use the full Python path:
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```json
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{
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"mcpServers": {
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"agentmem": {
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"command": "python",
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"args": ["-m", "agentmem", "--db", "./memory.db", "--project", "myproject", "serve"],
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"type": "stdio"
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}
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}
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}
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```
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On Windows, you may need the full Python path:
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```json
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{
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"mcpServers": {
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"agentmem": {
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"command": "C:/Python313/python.exe",
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"args": ["-m", "agentmem", "--db", "C:/path/to/memory.db", "--project", "myproject", "serve"],
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"type": "stdio"
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}
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}
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}
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```
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### Verify
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In Claude Code, the agentmem tools should show up. Ask Claude to run `memory_health` to confirm the connection.
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---
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## Cursor
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Cursor reads MCP config from `~/.cursor/mcp.json` (global) or `.cursor/mcp.json` (project root).
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Create or edit the file:
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```json
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{
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"mcpServers": {
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"agentmem": {
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"command": "agentmem",
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"args": ["--db", "./memory.db", "--project", "myproject", "serve"]
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}
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}
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}
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```
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If `agentmem` isn't on PATH, use the full Python path:
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```json
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{
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"mcpServers": {
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"agentmem": {
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"command": "python",
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"args": ["-m", "agentmem", "--db", "./memory.db", "--project", "myproject", "serve"]
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}
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}
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}
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```
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### Verify
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Open the command palette (`Ctrl+Shift+P` / `Cmd+Shift+P`), type "MCP", and check that agentmem appears as a connected server. You can also type "Open MCP Settings" to see the config.
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---
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## Codex (OpenAI)
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Codex reads MCP config from `~/.codex/config.toml` (global) or `.codex/config.toml` (project root, trusted projects only).
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Add this to the config file:
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```toml
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[mcp_servers.agentmem]
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command = "agentmem"
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args = ["--db", "./memory.db", "--project", "myproject", "serve"]
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```
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If `agentmem` isn't on PATH:
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```toml
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[mcp_servers.agentmem]
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command = "python"
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args = ["-m", "agentmem", "--db", "./memory.db", "--project", "myproject", "serve"]
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```
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### Verify
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Run `codex` and ask it to use the `memory_health` tool. If it returns a health score, you're connected.
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---
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## Windsurf
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Windsurf uses the same MCP config format as Cursor. Create `~/.windsurf/mcp.json` or `.windsurf/mcp.json` in your project:
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```json
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{
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"mcpServers": {
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"agentmem": {
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"command": "agentmem",
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"args": ["--db", "./memory.db", "--project", "myproject", "serve"]
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}
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}
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}
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```
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---
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## Available MCP Tools
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Once connected, your agent has 13 tools:
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| Tool | What it does |
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|------|-------------|
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| `add_memory` | Store a typed memory (bug, decision, setting, procedure, context, feedback) |
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| `search_memory` | Full-text search with filters |
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| `recall_memory` | Context-budgeted retrieval — fits best memories into a token limit |
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| `update_memory` | Update a memory by ID |
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| `delete_memory` | Delete a memory by ID |
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| `list_memories` | List memories with optional type filter |
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| `save_session` | Save current work state before conversation ends |
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| `load_session` | Restore state at the start of a new session |
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| `promote_memory` | Advance trust: hypothesis -> active -> validated |
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| `deprecate_memory` | Mark as no longer true (excluded from recall) |
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| `supersede_memory` | Replace old memory with new one |
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| `memory_health` | Score the memory system 0-100 |
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| `memory_conflicts` | Find contradictions between active memories |
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---
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## Tips
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**Start every session** by having your agent call `load_session`. This restores where the last session left off.
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**End every session** with `save_session`. Capture what's in progress, what's blocked, and what was decided.
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**Promote memories** that prove correct. A `validated` memory ranks higher than `active` in recall. A `hypothesis` ranks lowest. This is how your agent learns what to trust.
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**Run health checks** periodically. `memory_health` tells you if contradictions, stale rules, or orphaned references are degrading trust.
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**Use project scoping** if you work on multiple codebases. Each project gets isolated memory with `--project projectname`.
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---
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## Troubleshooting
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**Tools don't appear after config change**
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Restart your editor. MCP servers are loaded at startup.
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**"Command not found" errors**
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Use the full path to Python and `-m agentmem` instead of the `agentmem` command directly.
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**Windows path issues**
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Use forward slashes in JSON config: `C:/Users/you/memory.db`, not backslashes.
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**Server starts but no tools appear**
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Check that you have the MCP extra installed: `pip install quilmem[mcp]`. The base package doesn't include the MCP dependency.
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**Multiple agents sharing one database**
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Use different `--project` values. Each project's memories are isolated in search and recall, but stored in the same file.

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