pulsemcp Safe content atomic mcp-remote

Filesystem

This MCP server implements a comprehensive set of filesystem operations, enabling AI agents to interact with the host system's files and directories. Developed using Python and the FastMCP framework, it provides tools for navigation, reading, writing, and analyzing files, as well as a notes system for metadata. The implementation focuses on offering a wide range of file manipulation capabilities through a standardized interface, including batch operations for improved efficiency. It's particularly useful for AI-assisted file management, code analysis, and content generation tasks, allowing seamless integration of AI capabilities with local filesystem operations.

Cognium trust score

50%

Tier

Unverified

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

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Metadata

Version: 1.0.0
Skill type: atomic
Execution layer: mcp-remote
Category: ai-ml
Source: PulseMCP
Repository: github.com/kvas-it/mcp-server-fs
Author type: human
Updated: 2026-04-25

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MCP

Resolve Filesystem 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"