pulsemcp scanned Safe content atomic mcp-remote

Memory Inspector

Injects a DLL into 64-bit Windows processes to expose Cheat Engine-style memory analysis capabilities as MCP tools. Provides approximately 50 tools for reading and writing memory, scanning for values, disassembling code, analyzing data structures, and applying patches. Communicates through a Python bridge server over TCP on port 37651. Distributed as a compiled DLL plus Python script — no build step required for end users.

Cognium trust score

63%

Tier

Scanned

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 2026-09-01.

Scan details: Circle-IR · 2026-09-01 · Appeal

View full trust & usage report →

Metadata

Version: 1.0.0
Skill type: atomic
Execution layer: mcp-remote
Category: other
Source: PulseMCP
Repository: github.com/xieemengxin/memory-inspector-mcp
Author type: human
Last scanned: 2026-09-01
Updated: 2026-09-01

View source Find related skills

MCP

Resolve Memory Inspector 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"