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AWS Cost Explorer and Bedrock Usage Analytics

AWS Cost Explorer MCP Server provides a specialized interface for retrieving AWS cloud spending data and Amazon Bedrock usage statistics through CloudWatch logs. Developed by Amit Arora, this Python-based server exposes Cost Explorer API functionality and Bedrock model invocation logs as MCP tools, allowing detailed analysis of EC2 spending, service costs breakdowns, and Bedrock usage patterns by region, user, and model. The implementation supports both local deployment via Claude Desktop and remote operation on Amazon EC2, making it particularly valuable for AWS customers who need to monitor and analyze their cloud spending and AI model usage directly within Claude conversations.

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: cloud-infra
Source: PulseMCP
Repository: github.com/aarora79/aws-cost-explorer-mcp-server
Author type: human
Updated: 2026-04-25

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MCP

Resolve AWS Cost Explorer and Bedrock Usage Analytics 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"