FRENES

Monitoring and observability · MCP server

MCP server logs sieve: MCP server, setup and security

MCP server logs sieve is an open-source MCP server that lets an AI agent query, summarize and trace logs across providers using plain English. Its repository has 5 stars and its last commit is from October 9, 2026 and it is licensed under MIT.

Actively maintained

What MCP server logs sieve does

According to its repository: “Query, summarize and trace logs in plain English across GCP Cloud Logging, AWS CloudWatch, Azure Log Analytics, Grafana Loki and Elasticsearch.”

An MCP server gives an AI agent extra tools it calls during the conversation: the agent reads their description, decides to use them and gets the result back. MCP server logs sieve is listed under Monitoring and observability, a category of 57 servers in the directory, where it ranks #52 by stars.

Topics declared by the repository: cloud-providers, gcp, aws-cloudwatch, mcp-tools, azure, azuremonitor.

Installing and connecting MCP server logs sieve

No package or remote server is declared in the official MCP registry: you install it from source, following the repository README.

Like any MCP server, you declare it in your client's configuration (Claude Desktop, Claude Code, Cursor, VS Code, Codex…): a name, the command that starts it or its URL, and any environment variables. The client then starts it and lists its tools. Project language: TypeScript. Listed systems: macOS, Windows, Linux.

Security: what to check

An MCP server runs code with the rights you give it, and the model reads its tool descriptions: a malicious or compromised server can hijack the agent. Read the code, or pick a maintained and widely used server, before connecting it.

None of the risk signals we track (system access, secrets, missing licence, abandonment) applies to MCP server logs sieve. That does not replace reading the code.

Good practice: grant only the rights needed (least privilege), require human approval for irreversible actions, and run the AI agent security check.

Project activity and maintenance

Created on May 28, 2025, the Oluwatunmise-olat/mcp-server-logs-sieve repository has 5 stars and 1 forks, with 0 open issues. It has more stars than 13% of the servers in the directory. It received changes this month.

Stars measure attention, not quality: a recent, heavily promoted project can collect them fast, while a useful but niche server will have few.

NetdataNetdata : 81.1K81.1KOpenstatusOpenstatus : 9.2K9.2KOneUptimeOneUptime : 7.8K7.8KMCP grafanaMCP grafana : 3.6K3.6KMarmot Data CatalogMarmot Data Catalog : 623623Watch skillWatch skill : 520520HomebutlerHomebutler : 305305Zabbix MCP serverZabbix MCP server : 261261MCP server logs sieveMCP server logs sieve : 55
GitHub stars of the most followed servers in the category (log scale); MCP server logs sieve in orange. Checked October 25, 2026.

Verdict

MCP server logs sieve is a reasonable choice; check the points below before connecting it.

Strengths

  • Active project: recent commit
  • Permissive licence (MIT)

Limitations

  • Few visible users
  • Install from source

Frequently asked questions

How do I install MCP server logs sieve?

No package is declared in the MCP registry: clone the Oluwatunmise-olat/mcp-server-logs-sieve repository, follow its README, then declare the start command in your client's MCP configuration.

Is MCP server logs sieve free?

The code is published under the MIT licence and can be used free of charge.

Is MCP server logs sieve safe?

No risk signal found (system access, secrets, licence, abandonment). As with any MCP server, keep rights minimal and read the code before sensitive use.

Is it an official server?

Nothing says so: it is a project published by Oluwatunmise-olat on GitHub. Check who maintains it before giving it access.

What are the alternatives to MCP server logs sieve?

In the same category: Netdata, MCP grafana, Openstatus, and OneUptime. Netdata and MCP grafana score higher on our grid.

Related articles

Neutrality. No affiliate links. No vendor pays to be reviewed, rated or ranked. Reviews are directed by François Chollet, neutral and factual, and every data point is dated and sourced. How we score