Attestor runs on your own machine — the client starts it, so there is no endpoint to ping. 252 installs a week from pypi. Last commit 30 May 2026.
Self-hosted memory for agent teams. Bi-temporal replay, deterministic retrieval, audit log.
We read the source, 20 h ago · rules 3dff92dd89df
What this server is able to do. For an MCP server this is often the job itself — a terminal server runs commands because that is what it is for. Listed so you know what you are plugging in, not as an accusation.
proc = subprocess.run(cmd, capture_output=True, text=True, timeout=180)
path = os.path.join(home, ".claude", "projects", slug, f"{session_id}.jsonl")
<select class="field" name="status">
<option value="active" {% if filters.status == 'active' %}selected{% endif %}>active</option>
Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.
We found places where it runs commands, builds paths or queries from values it is given. None of that is a flaw by itself — it becomes one when the code changes, and code changes quietly between releases. We re-read it on every one.
This server runs on your own machine — install it with the package manager and the client starts it for you. Package name taken from the official registry entry.
claude mcp add attestor -- uvx attestor
{
"mcpServers": {
"attestor": {
"args": [
"attestor"
],
"command": "uvx"
}
}
}
[mcp_servers.attestor]
command = "uvx"
args = ["attestor"]
{
"mcpServers": {
"attestor": {
"args": [
"attestor"
],
"command": "uvx"
}
}
}
{
"mcpServers": {
"attestor": {
"args": [
"attestor"
],
"command": "uvx"
}
}
}
This one needs environment variables set before it will start:
ATTESTOR_PATH (Directory containing attestor's config.toml. Defaults to ~/.attestor.), ATTESTOR_DISABLE_LOCAL_EMBED (Set to 1 to skip the local Ollama embedder probe (e.g., on hosts without Ollama). Defaults to unset (Ollama is the default embedder).), OPENAI_API_KEY (OpenAI API key (used for the OpenAI text-embedding-3-large fallback embedder when Ollama is unavailable).), OPENROUTER_API_KEY (OpenRouter API key (used for the federated LLM extraction / consolidation paths and for the LongMemEval benchmark runner).).
The author declared them in the registry entry; get the values from the project itself.
Self-hosted, source-traceable memory layer and MCP server for AI agents, on your own Postgres.
Free spend report from an agent log, no key. Hosted proxies: caps, audit export, buy calls.
100 deterministic tools for your AI: logs, tests, SQL, diagrams, SPARQL. Local, no network.
Local-first secret scanning, rotation, vault, and audit-log tools for AI agents.
PlatformIO for AI agents: build, flash, serial monitor, tests, crash decoding, size reports.
Safe Google Workspace admin for AI agents: read-only by default, confirm-gated deletes, audit log.
Project memory across sessions for AI agents. A queryable decision log in the repo.
Reduces log files for AI consumption — 50-90% token reduction via 18 deterministic transforms.
Answers built from our own checks of this server.