mcpbeat Sign in

Seam Runtime MCP Server

by blackhatshiftey Your server? Claim it
local only

Seam Runtime runs on your own machine — the client starts it, so there is no endpoint to ping. 34 installs a week from pypi.

SEAM: local-first memory runtime for AI agents, with retrieval and glassbox provenance over MCP.

The linked repository no longer exists on GitHub — it was deleted or made private.

Installs per day peak 12 · avg 5 · -24% w/w
a month agotoday
34
Installs / week
pypi · seam-runtime
—
Stars
on GitHub
—
Last commit
from GitHub
—
License
language unknown

This one has been quiet for a while

Quiet is not dead — but it is worth knowing when it wakes up, or when someone else takes it over. We watch the repository and tell you either way.

Three servers free · no card

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.

run in your terminal
claude mcp add seam-runtime -- uvx seam-runtime
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "seam-runtime": {
      "command": "uvx",
      "args": [
        "seam-runtime"
      ]
    }
  }
}
~/.codex/config.toml
[mcp_servers.seam-runtime]
command = "uvx"
args = ["seam-runtime"]
.cursor/mcp.json
{
  "mcpServers": {
    "seam-runtime": {
      "command": "uvx",
      "args": [
        "seam-runtime"
      ]
    }
  }
}
.vscode/mcp.json
{
  "servers": {
    "seam-runtime": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "seam-runtime"
      ]
    }
  }
}

Optional settings from the registry entry, left out of the block above: SEAM_DB_PATH (Path to the local SQLite memory database. Defaults to a per-user data directory if unset), SEAM_PGVECTOR_DSN (Optional Postgres/pgvector DSN for the vector adapter. If unset, SEAM runs on the built-in SQLite vector store).

Alternatives to Seam Runtime

same job, measured the same way
Tacitus MCP Server
by ionasrobert

Long-term memory for AI agents: local-first PKM with provenance and hybrid search.

61 installs/wk local only
kala-mcp
by anusornc

kala memory over MCP: provenance-first agent memory with Datalog recall and as-of time travel.

local only
Cluefinch MCP
by cluefinch

Local-first web research for AI agents with SearXNG search and SSRF-safe page retrieval.

49 installs/wk local only
Neurakeep
by dominiclachance

Local-first, source-cited memory for AI agents with proposal review, failure memory, and MCP tools.

275 installs/wk local only
Memkeeper
by teflon07

Local-first memory for AI agents: on-device hybrid retrieval over a single SQLite file.

local only
Kairn
by primeline-ai

Local-first knowledge engine for AI agents: memory, graph, and recall over MCP.

local only
Cozo Memory
by tobs-code

Local-first memory system for AI agents with hybrid search and graph reasoning

43 installs/wk local only
rmbr
by srock44

Embedded, local-first memory and retrieval for AI agents. One SQLite file, no server, no API key.

91 installs/wk local only

Seam Runtime — questions

Answers built from our own checks of this server.

Why is there no uptime for Seam Runtime?
Seam Runtime runs on your own machine over stdio — there is no network address to reach, so uptime cannot be measured for it by anyone. What can be measured is adoption: the pypi package seam-runtime was installed 34 times last week.
Is Seam Runtime still maintained?
The linked repository no longer exists on GitHub — it was deleted or made private. We show this because it changes what you can expect: an unmaintained server may keep answering for months and then stop without warning.
How do I connect Seam Runtime?
Copy the ready config from this page. We generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each in the form that client actually reads. It runs locally, so the command pulls seam-runtime straight from pypi; nothing to host, nothing to sign up for.
How many people use Seam Runtime?
The pypi package seam-runtime was installed 34 times in the last week. Week over week that is -24%. We show installs rather than GitHub stars on purpose: a star is a bookmark, an install is someone actually running it.