Search / io.github.volsier/memforge-memory
memforge-memory
L0· runs locallyTeam engineering memory for AI coding assistants. 47 MCP tools, pgvector semantic search.
v1.0.1 · active · descriptor JSON · versions
Search / io.github.volsier/memforge-memory
L0· runs locallyTeam engineering memory for AI coding assistants. 47 MCP tools, pgvector semantic search.
v1.0.1 · active · descriptor JSON · versions
{
"mcpServers": {
"memforge-memory": {
"command": "npx",
"args": [
"-y",
"@memforgeai/[email protected]"
],
"env": {
"DATABASE_URL": "${DATABASE_URL}",
"OPENAI_BASE_URL": "${OPENAI_BASE_URL}",
"OPENAI_API_KEY": "${OPENAI_API_KEY}",
"OPENAI_EMBEDDING_MODEL": "${OPENAI_EMBEDDING_MODEL}"
}
}
}
}claude mcp add memforge-memory -e "DATABASE_URL=${DATABASE_URL}" -e "OPENAI_BASE_URL=${OPENAI_BASE_URL}" -e "OPENAI_API_KEY=${OPENAI_API_KEY}" -e "OPENAI_EMBEDDING_MODEL=${OPENAI_EMBEDDING_MODEL}" -- npx -y @memforgeai/[email protected][mcp_servers.memforge-memory]
command = "npx"
args = ["-y", "@memforgeai/[email protected]"]
env = { "DATABASE_URL" = "${DATABASE_URL}", "OPENAI_BASE_URL" = "${OPENAI_BASE_URL}", "OPENAI_API_KEY" = "${OPENAI_API_KEY}", "OPENAI_EMBEDDING_MODEL" = "${OPENAI_EMBEDDING_MODEL}" }
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"memforge-memory": {
"type": "local",
"command": [
"npx",
"-y",
"@memforgeai/[email protected]"
],
"enabled": true,
"environment": {
"DATABASE_URL": "{env:DATABASE_URL}",
"OPENAI_BASE_URL": "{env:OPENAI_BASE_URL}",
"OPENAI_API_KEY": "{env:OPENAI_API_KEY}",
"OPENAI_EMBEDDING_MODEL": "{env:OPENAI_EMBEDDING_MODEL}"
}
}
}
}{
"mcpServers": {
"memforge-memory": {
"command": "npx",
"args": [
"-y",
"@memforgeai/[email protected]"
],
"env": {
"DATABASE_URL": "${DATABASE_URL}",
"OPENAI_BASE_URL": "${OPENAI_BASE_URL}",
"OPENAI_API_KEY": "${OPENAI_API_KEY}",
"OPENAI_EMBEDDING_MODEL": "${OPENAI_EMBEDDING_MODEL}"
}
}
},
"deeplink": "cursor://anysphere.cursor-deeplink/mcp/install?name=memforge-memory&config=eyJjb21tYW5kIjoibnB4IiwiYXJncyI6WyIteSIsIkBtZW1mb3JnZWFpL21lbW9yeS1zZXJ2aWNlQDEuMC4xIl0sImVudiI6eyJEQVRBQkFTRV9VUkwiOiIke0RBVEFCQVNFX1VSTH0iLCJPUEVOQUlfQkFTRV9VUkwiOiIke09QRU5BSV9CQVNFX1VSTH0iLCJPUEVOQUlfQVBJX0tFWSI6IiR7T1BFTkFJX0FQSV9LRVl9IiwiT1BFTkFJX0VNQkVERElOR19NT0RFTCI6IiR7T1BFTkFJX0VNQkVERElOR19NT0RFTH0ifX0%3D"
}{
"servers": {
"memforge-memory": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@memforgeai/[email protected]"
],
"env": {
"DATABASE_URL": "${DATABASE_URL}",
"OPENAI_BASE_URL": "${OPENAI_BASE_URL}",
"OPENAI_API_KEY": "${OPENAI_API_KEY}",
"OPENAI_EMBEDDING_MODEL": "${OPENAI_EMBEDDING_MODEL}"
}
}
}
}{
"mcpServers": {
"memforge-memory": {
"command": "npx",
"args": [
"-y",
"@memforgeai/[email protected]"
],
"env": {
"DATABASE_URL": "${DATABASE_URL}",
"OPENAI_BASE_URL": "${OPENAI_BASE_URL}",
"OPENAI_API_KEY": "${OPENAI_API_KEY}",
"OPENAI_EMBEDDING_MODEL": "${OPENAI_EMBEDDING_MODEL}"
}
}
}
}extensions:
"memforge-memory":
enabled: true
name: "memforge-memory"
type: stdio
cmd: "npx"
args:
- "-y"
- "@memforgeai/[email protected]"
envs:
"DATABASE_URL": "${DATABASE_URL}"
"OPENAI_BASE_URL": "${OPENAI_BASE_URL}"
"OPENAI_API_KEY": "${OPENAI_API_KEY}"
"OPENAI_EMBEDDING_MODEL": "${OPENAI_EMBEDDING_MODEL}"
timeout: 300
Placeholders to fill from your own secret store: ${OPENAI_API_KEY}. The registry never accepts secret values.
This is a local package: the command runs on your machine.
Not scored: fewer than three checks apply, usually because no remote answered a credential-free probe or the server is a local package.
protocol.modern, protocol.stateless, protocol.transport, protocol.list_ttlno remote answered a protocol handshake (not probed yet, unreachable, or local-only)auth.prm, auth.as_metadata, auth.cimdno remote uses OAuthauth.secret_in_urlno templated URLtools.descriptions, tools.description_length, tools.schemas, tools.annotations, tools.directory_hints, tools.token_cost, tools.api_dumptool list unknown (behind auth, not probed, or empty)stability.changes, stability.rug_pulltool list unknowndeps.known_vulnsno known advisory in 99 resolved packagesdeps.mcp_sdk_version@modelcontextprotocol/sdk 1.30.1 has 1 known advisory (GHSA-6qxp-vccf-f47h); update @modelcontextprotocol/sdk to 1.31.0 or laterdeps.resolvablethe dependency graph of @memforgeai/[email protected] resolved with errors, so advisories may be missingNo tool definition changes recorded. A server's first observation is its baseline; later probes record what changes.
Checks run on what our credential-free, read-only probes observe; tools are never called and no code audit is performed. How it is computed.
~liveness-unmeasured ~updated-179d-ago -no-repository
Derived from observable signals (official registry feed and our own credential-free probes); no code audit performed. How it is computed.
@memforgeai/[email protected] npm98 dependencies, resolved with errors, so advisories may be missing · MCP SDK @modelcontextprotocol/sdk 1.30.1 · advisories checked 2026-10-19
| advisory | severity | package | fixed in |
|---|---|---|---|
| GHSA-6qxp-vccf-f47hMCP TypeScript SDK: OAuth client could send credentials to an authorization server chosen by the MCP server | high | @modelcontextprotocol/[email protected]MCP SDK, direct | fixed in 1.31.0 |
Dependency graphs from deps.dev; advisories from OSV.dev, including the GitHub Advisory Database and the PyPI Advisory Database; all CC BY 4.0. The graph is what a clean install of this version resolves today; nothing was installed or run. How it is checked.
| package | registry | version | runtime | secrets |
|---|---|---|---|---|
@memforgeai/memory-service | npm | 1.0.1 | – | OPENAI_API_KEY |
No tools observed. Local packages are never executed by the registry.
Schemas: list_tools.
{
"name": "io.github.volsier/memforge-memory",
"$schema": "https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json",
"version": "1.0.1",
"packages": [
{
"version": "1.0.1",
"transport": {
"type": "stdio"
},
"identifier": "@memforgeai/memory-service",
"registryType": "npm",
"environmentVariables": [
{
"name": "DATABASE_URL",
"isRequired": true,
"description": "PostgreSQL connection string"
},
{
"name": "OPENAI_BASE_URL",
"isRequired": true,
"description": "Embedding API base URL (OpenAI-compatible)"
},
{
"name": "OPENAI_API_KEY",
"isSecret": true,
"isRequired": true,
"description": "Embedding API key"
},
{
"name": "OPENAI_EMBEDDING_MODEL",
"isRequired": true,
"description": "Embedding model name (e.g. BAAI/bge-m3)"
}
]
}
],
"description": "Team engineering memory for AI coding assistants. 47 MCP tools, pgvector semantic search."
}