pulsemcp verified Safe content atomic mcp-remote

MemProcFS

MemProcFS-mcp-server provides a bridge between AI assistants and memory forensics capabilities through the MemProcFS Python library. The server exposes tools for analyzing process attributes, registry hives, keys and values from memory dumps, making it valuable for digital forensics investigators who need to examine Windows memory images through natural language interaction. Built with FastMCP, it features robust error handling and comprehensive documentation of available process and registry attributes.

Cognium trust score

97%

Tier

Verified

Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-28.

Scan details: Circle-IR · 2026-09-28 · Appeal

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Metadata

Version: 1.0.0
Skill type: atomic
Execution layer: mcp-remote
Category: media
Source: PulseMCP
Repository: github.com/tokeii0/memprocfs-mcp-server
Author type: human
Last scanned: 2026-09-28
Updated: 2026-09-28

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MCP

Resolve MemProcFS from your agent

Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.

One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.

claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp

Swap --scope user for --scope project to commit it to .mcp.json.

Your client Same endpoint everywhere; only the config key differs. The full list is in the descriptor.

Claude Desktop · Settings → Connectors → Add custom connector

https://api.skillsregistry.net/mcp

Paste the URL as the connector endpoint. No authentication.

ChatGPT · Settings → Connectors → Create (developer mode) → MCP server URL

https://api.skillsregistry.net/mcp

Authentication: none. Works in chat and deep research — the server exposes the connector search and fetch tools.

Codex CLI · ~/.codex/config.toml

[mcp_servers.skillsregistry]
url = "https://api.skillsregistry.net/mcp"