Waggle MCP runs on your own machine — the client starts it, so there is no endpoint to ping. 54 installs a week from pypi. Last commit 17 Sep 2026.
Persistent graph-backed conversational memory for AI agents.
We read the source, 21 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.
этот файл ставится пользователю, но в репозитории его нет
execFile(command, args, mergedOptions, (error, stdout, stderr) => {
result = subprocess.run(
context_path = os.path.join(self.temp_dir, f"context_{context_index}.txt")
exec(code, combined, combined)
for (const [key, value] of Object.entries(process.env)) {
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 Waggle-mcp -- uvx waggle-mcp
{
"mcpServers": {
"Waggle-mcp": {
"args": [
"waggle-mcp"
],
"command": "uvx"
}
}
}
[mcp_servers.Waggle-mcp]
command = "uvx"
args = ["waggle-mcp"]
{
"mcpServers": {
"Waggle-mcp": {
"args": [
"waggle-mcp"
],
"command": "uvx"
}
}
}
{
"mcpServers": {
"Waggle-mcp": {
"args": [
"waggle-mcp"
],
"command": "uvx"
}
}
}
This one needs environment variables set before it will start:
WAGGLE_TRANSPORT (Transport mode for the MCP server.), WAGGLE_BACKEND (Backend database type: sqlite for local use or neo4j for service deployments.), WAGGLE_DB_PATH (Path to the SQLite memory database when WAGGLE_BACKEND is sqlite.), WAGGLE_DEFAULT_TENANT_ID (Default tenant ID for local or shared memory isolation.), WAGGLE_MODEL (Sentence-transformers model used for local embeddings.).
The author declared them in the registry entry; get the values from the project itself.
Persistent memory for AI agents — verbatim conversations, searchable by meaning.
Persistent memory for AI agents — log and recall conversation context over MCP.
Persistent, evidence-backed code graph for coding agents.
Persistent institutional memory for AI coding agents. Memory that compounds.
Local-first persistent memory for AI coding agents.
Graph-native memory for AI agents: a knowledge graph built from conversation, via MCP.
Persistent file-based memory for AI agents: inspectable, versionable, fully local.
MCP server for persistent, searchable memory for AI agents.
Answers built from our own checks of this server.