Lightweight logging & observability for agent work across clients (Codex, Claude, Cursor, ChatGPT, OpenClaw, and others). - One MCP tool (logwork) that aggregates work done across different agents for single or multiple users. - Define your own logging structure with custom schemas (or use built-in profiles) once, and the MCP schema will guide clients to log with correct payloads. - This lets team
Add this skill
npx mdskills install ejcho623/agent-breadcrumbsWell-documented MCP server providing configurable logging across multiple agent clients with flexible output sinks
Lightweight logging & observability for agent work across clients (Codex, Claude, Cursor, ChatGPT, OpenClaw, and others).
https://github.com/user-attachments/assets/3eac31a8-107c-4a82-a14c-dcfa500dd1a9
log_work) that aggregates work done across different agents for single or multiple users.packages/mcpapps/dashboardInstall and run with defaults:
npx -y agent-breadcrumbs
Use with an explicit config file:
npx -y agent-breadcrumbs --config /absolute/path/to/server-config.json
~/.codex/config.toml):[mcp_servers.agent_breadcrumbs]
command = "npx"
args = ["-y", "agent-breadcrumbs", "--config", "/absolute/path/to/server-config.json"]
--config is optional. If omitted, server defaults are used:
claude_desktop_config.json):{
"mcpServers": {
"agent-breadcrumbs": {
"command": "npx",
"args": ["-y", "agent-breadcrumbs", "--config", "/absolute/path/to/server-config.json"]
}
}
}
After you install the MCP server make sure to use mcporter so the server can be called through the CLI. Then add a system prompt to the channel you're using.
For cron-driven workflows, instruct agents to call log_work on each scheduled run for regular time-based logging.
Every hour, make sure to use mcporter agent-breadcrumbs.log_work to log work.
If spinning up a cron job, make sure to add this context (e.g., logging work every hour) in the cron job description as well.
General example global instruction/system prompt for clients:
When a meaningful chunk of work is completed, use log_work with agent_breadcrumbs to record your work.
For full MCP server setup, config, and sink details, see packages/mcp/README.md.
npm install
npm run build:all
Run MCP server locally with a sample config:
node packages/mcp/dist/index.js --config packages/mcp/examples/server-config.agent-insights.sample.json
Run dashboard locally:
npm run dev:dashboard -- --config apps/dashboard/examples/dashboard-config.sample.json
Top-level config file is JSON and supports:
schema for fully custom log_record properties, orschema_profile for built-in profile files in packages/mcp/examples/schema_profilesuser_name for server-side user identity injection into persisted recordssink for destination settings (jsonl, webhook, postgres)Do not set both schema and schema_profile together.
Default behavior when omitted:
agent_id, timestamp, work_summary, additional)jsonl~/.agent-breadcrumbs/logs.jsonllog_record fields from the tool definition.npm run build:mcp
npm run dev:mcp
npm run test
npm run test:integration
npm run build:dashboard
npm run dev:dashboard
packages/mcp/README.mdapps/dashboard/README.mdInstall via CLI
npx mdskills install ejcho623/agent-breadcrumbsAgent Breadcrumbs ๐ is a free, open-source AI agent skill. Lightweight logging & observability for agent work across clients (Codex, Claude, Cursor, ChatGPT, OpenClaw, and others). - One MCP tool (logwork) that aggregates work done across different agents for single or multiple users. - Define your own logging structure with custom schemas (or use built-in profiles) once, and the MCP schema will guide clients to log with correct payloads. - This lets team
Install Agent Breadcrumbs ๐ with a single command:
npx mdskills install ejcho623/agent-breadcrumbsThis downloads the skill files into your project and your AI agent picks them up automatically.
Agent Breadcrumbs ๐ works with Claude Code, Claude Desktop, Cursor, Vscode Copilot, Windsurf, Continue Dev, Codex, Gemini Cli, Amp, Roo Code, Goose, Opencode, Trae, Qodo, Command Code, Chatgpt. Skills use the open SKILL.md format which is compatible with any AI coding agent that reads markdown instructions.