Particles runs on your own machine — the client starts it, so there is no endpoint to ping. 1 864 installs a week from pypi. Last commit 2 Nov 2026.
An append-only ledger of sourced, dated, confidence-scored claims your agent cites and you audit
What the code does
We read the source, 1 d ago · rules 995398eba69f
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.
setup.py: выполняет код при установке пакета
done = subprocess.run( # noqa: S603 — fixed argv, no shell
Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.
This code can reach further than it looks
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.
Connect this server
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 particles -e 'ANTHROPIC_API_KEY=<ANTHROPIC_API_KEY>' -- uvx linkedparticles{
"mcpServers": {
"particles": {
"command": "uvx",
"args": [
"linkedparticles"
],
"env": {
"ANTHROPIC_API_KEY": "<ANTHROPIC_API_KEY>"
}
}
}
}[mcp_servers.particles]
command = "uvx"
args = ["linkedparticles"]
env = { ANTHROPIC_API_KEY = "<ANTHROPIC_API_KEY>" }{
"mcpServers": {
"particles": {
"command": "uvx",
"args": [
"linkedparticles"
],
"env": {
"ANTHROPIC_API_KEY": "<ANTHROPIC_API_KEY>"
}
}
}
}{
"servers": {
"particles": {
"type": "stdio",
"command": "uvx",
"args": [
"linkedparticles"
],
"env": {
"ANTHROPIC_API_KEY": "<ANTHROPIC_API_KEY>"
}
}
}
}Put your own value in place of
<ANTHROPIC_API_KEY> (Anthropic API key. Required for the tools that call a model — `query` composes a cited natural-language answer, and the semantic half of `lint` reasons over claim pairs. The accessors that only read the store (`particle_show`, `particles_list`, `subjects_*`, `events_*`, `graph_view`, `quality_report`) work without it).
The author’s registry entry marks it as required.
Optional settings from the registry entry, left out of the block above:
DATABASE_URL (SQLAlchemy URL of the belief store to serve, used as given, so write a SQLite path absolute: a relative one opens against the directory the server starts in. Without it, and without PARTICLES_CONFIG, the server serves the store `~/.particles/config.yaml` names (a relative path there is read under `~/.particles/`), or `~/.particles/particles.db` when that file names none, never a store in the directory it starts in), PARTICLES_CONFIG (Path to the config file holding the rest of the server's settings: additional stores, model selection per purpose, and the `mcp.write.enabled_stores` allowlist that turns the write tools on. This is the supported way to give the server settings. Without it the server reads `~/.particles/config.yaml`, never a `config.yaml` in the directory it starts in. Give it as an absolute path: a relative one is refused. When you set it, also set `DATABASE_URL` to an absolute path or name one as `storage.database_url` in the file: a server started with a config file refuses a store path relative to its working directory, and refuses to start while any store under `storage.stores` has one).
Alternatives to Particles
same job, measured the same wayScore and improve your AI coding agent setup. Local-only, open source.
The agent switchboard: identity, policy, loop-guard, and an append-only audit ledger.
Evaluate your agent's context for unreliable sources, dependencies, redundant and stale claims.
Dated, sourced claims about AI crawlers and agents, offered as MCP tools.
Research, draft and score cited SEO articles with claim-level evidence and hard quality gates.
Source-cited ARRMA 3S / 4x4 parts fitment with revision scope, confidence, sources, and guides.
Scan, enumerate, and risk-score every MCP server configured on your machine.
Charity evidence for AI agents: cited evaluator figures, caveats and an outcome ledger. Read-only.
Particles — questions
Answers built from our own checks of this server.