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FastMCP Supply Chain Optimizer

FastMCP server implementation by ANSH-RIYAL that demonstrates real-time supply chain optimization using Google Gemini AI for intelligent decision-making across inventory management, warehouse transfers, and reorder recommendations. The implementation processes supply chain events (demand spikes, delays, cost increases) from CSV data through a Flask web interface, using MCP tools for inventory status checking, stock transfer calculations, stockout predictions, and automated reorder suggestions, with Gemini AI analyzing events and executing parallel tool calls for optimization decisions. Built with a complete web dashboard featuring terminal output and action logging, it serves as both a functional supply chain management system and a demonstration of how MCP can integrate AI-powered decision-making with real-time business operations, making it valuable for supply chain managers, logistics coordinators, and developers building AI-driven inventory optimization systems.

Cognium trust score

100%

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 2026-09-19.

Scan details: Circle-IR · 2026-09-19 · Appeal

View full trust & usage report →

Metadata

Version: 1.0.0
Skill type: atomic
Execution layer: mcp-remote
Category: data-analytics
Source: PulseMCP
Repository: github.com/ansh-riyal/fastmcp
Author type: human
Last scanned: 2026-09-19
Updated: 2026-09-19

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MCP

Resolve FastMCP Supply Chain Optimizer 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"