pathmark
Allows the server to use Ollama (or any OpenAI-compatible local gateway) as a synthesis provider for ask_memory, via the openai-compatible mode.
Allows the server to use OpenAI-compatible chat completion APIs for memory synthesis via the ask_memory tool, using the PATHMARK_OPENAI_BASE_URL and API key.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@pathmarkremember that I prefer using TypeScript for new projects"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Pathmark Memory
Local-first memory for MCP clients.
Pathmark Memory gives agent tools a shared, durable memory without requiring a hosted account, a vector database, or an API key. It runs as a standard Model Context Protocol server, so the same local memory can be used from Codex, Claude Code, opencode, Gemini CLI, OpenClaw, Hermes Agent, Grok-compatible MCP clients, Cursor, Claude Desktop, and other tools that can launch stdio MCP servers.
Why this exists
Most agent memory systems are tied to one product, one hosted backend, or one subscription. Pathmark is intentionally small:
Local JSONL store by default.
Standard MCP tools instead of a proprietary client.
Works when the model lives in the MCP client.
Optional subscription CLI bridge for server-side synthesis.
Optional OpenAI-compatible API bridge for Kimi, GLM, OpenRouter, local gateways, and other compatible providers.
Easy to inspect, back up, delete, or migrate.
Pathmark is provider-neutral. Codex is one optional synthesis preset, but the core server works with any MCP client that can use local tools.
Related MCP server: auxly-memory-cli
Tools
Pathmark exposes these MCP tools:
Tool | Purpose |
| Save a raw memory item. |
| Save a higher-signal durable conclusion or preference. |
| Search memories and conclusions. |
| Return compact context for a task or question. |
| List saved conclusions. |
| Soft-delete a memory or conclusion by id. |
| Return relevant context, or synthesize with |
| Show local store configuration. |
Quick Start
npm install -g github:hacksurvivor/pathmarkThen add the MCP server to your client.
The npm package name pathmark is currently available, but this first release is GitHub-only until npm publishing is explicitly done.
See docs/compatibility.md for Codex, Claude Code, opencode, Gemini CLI, OpenClaw, Hermes Agent, Grok CLI, Kimi, GLM, and generic MCP setups.
Codex
codex mcp add pathmark -- pathmarkClaude Desktop
Add this to your Claude Desktop MCP config:
{
"mcpServers": {
"pathmark": {
"command": "pathmark",
"env": {
"PATHMARK_STORE_DIR": "~/.pathmark/memory"
}
}
}
}Cursor
Add the same command to Cursor's MCP server settings:
{
"mcpServers": {
"pathmark": {
"command": "pathmark"
}
}
}Local Development
npm install
npm run build
npm run smokeRun directly:
PATHMARK_STORE_DIR=.pathmark npm run devConfiguration
Variable | Default | Description |
|
| Directory for |
|
| Default search limit. |
|
|
|
| unset | Command provider: receives a synthesized prompt on stdin and writes an answer on stdout. |
|
| Codex provider command. |
| unset | Optional Codex model override. |
|
| OpenAI-compatible API base URL. |
| unset | OpenAI-compatible API key. |
| unset | Model id for OpenAI-compatible synthesis. |
|
| Synthesis command timeout. |
Synthesis Modes
Pathmark separates memory from reasoning.
client
Default. The MCP server returns relevant memory context, and your MCP client model synthesizes the answer. This works across Codex, Claude Desktop, Cursor, and any other MCP client without giving Pathmark a model credential.
PATHMARK_SYNTHESIS_PROVIDER=client pathmarkcommand
Use any local subscription or model CLI that accepts a prompt on stdin and writes an answer to stdout:
PATHMARK_SYNTHESIS_PROVIDER=command \
PATHMARK_CHAT_COMMAND="your-ai-cli --model your-model" \
pathmarkThis is the general path for users with another paid subscription CLI or a local model runner.
codex
Use the proven Codex CLI bridge. It runs a controlled, non-interactive codex exec turn with hooks and memories disabled to avoid recursion:
PATHMARK_SYNTHESIS_PROVIDER=codex \
PATHMARK_CODEX_MODEL=gpt-5.5 \
pathmarkThis is useful for Codex users who have ChatGPT/Codex subscription auth locally but do not want to add an OpenAI API key.
openai-compatible
Use any provider that exposes /chat/completions, including many Kimi, GLM/Z.ai, OpenRouter, LiteLLM, Ollama-compatible gateways, and self-hosted routers:
PATHMARK_SYNTHESIS_PROVIDER=openai-compatible \
PATHMARK_OPENAI_BASE_URL=https://api.provider.example/v1 \
PATHMARK_OPENAI_API_KEY=... \
PATHMARK_OPENAI_MODEL=... \
pathmarkThis mode only affects ask_memory. Regular MCP tools still store and retrieve local memory without a model provider.
Data Format
Pathmark stores newline-delimited JSON at:
~/.pathmark/memory/memory.jsonlEach record is inspectable:
{
"id": "uuid",
"kind": "memory",
"text": "The user prefers local-first tools.",
"tags": ["preference"],
"source": "mcp",
"createdAt": "2026-06-29T00:00:00.000Z",
"updatedAt": "2026-06-29T00:00:00.000Z"
}Deletes are soft deletes: the record gets a deletedAt timestamp.
Roadmap
Codex installer for hooks, capture, and nudge behavior.
Provider presets for common local AI CLIs where stable commands exist.
Import/export commands for other memory systems.
Better ranking with optional local embeddings.
Namespaces for projects, teams, and clients.
Encrypted store option.
Hosted sync as an opt-in layer, not a requirement.
Example recipes for Codex, Claude Desktop, Cursor, ChatGPT, and local LLM tools.
Positioning
Pathmark is not trying to be a full agent platform. It is the memory layer: a small MCP server that gives agents a persistent working memory the user owns.
The public hook is simple:
Bring your own subscription. Keep your memory local.
License
MIT
Maintenance
Resources
Unclaimed servers have limited discoverability.
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If you are the server author, to access and configure the admin panel.
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