Okay, so not “Gemini Code Assist” but sufficiently similar that I think it warrants the “3/3” appellation.

I’m not a huge fan of all the se Node.JS-based CLI tools but, Google has released Gemini CLI. It’s good to have a CLI-based tool and it feels otherwise similar to the “Gemini Code Assist” chat.

I don’t (want to) run Node.JS on my Linux host and so am using the containerized version of the CLI here. It’s all documented on the gemini-cli repo but the auth functionality is sub-optimal (see [#1437] ) and you’ll want to use an API key if you can (see below):

Solved!

Ugh.

Before I continue, one important detail from yesterday’s experience which I think I didn’t clarify is that, unlike the Copilot agent, it appears (!?) that Gemini agent only supports integration with MCP servers via stdio. As a result, the only way to integrate with HTTP-based MCP servers (local or remote) is to proxy traffic through stdio as mcp-remote and the Rust example herein.

The most helpful change was to take a hint from the NPM mcp-remote and create a log file. This helps because, otherwise the mcp-remote process, because it’s launched by Visual Studio Code, well Gemini Code Assist agent, isn’t trivial to debug.

Former Microsoftie and Googler:

Good documentation Extend your agent with Model Context Protocol

Not such good documentation: Using agentic chat as a pair programmer

Definition of “good” being, I was able to follow the clear instructions and it worked first time. Well done, Microsoft!

This space is moving so quickly and I’m happy to alpha test these companies’ solutions but (a) Google’s portfolio is a mess. This week I’ve tried (and failed) to use Gemini CLI (because I don’t want to run Node.JS on my host machine and it doesn’t work in a container: issue #1437) and now this.

I couldn’t summarize this in a title (even with an LLM’s help):

I wanted to:

1. Run a Tailscale service discovery agent
2. On a Tailscale node outside of the Kubernetes cluster
3. Using Podman Quadlet
4. Accessing it from the Kubernetes Cluster using the Tailscale’s egress proxy
5. Accessing the proxy with a kube-prometheus ScrapeConfig
6. In order that Prometheus would scrape the container for Tailscale client metrics

Long-winded? Yes but I had an underlying need in running the Tailscale Service Discoovery remotely and this configuration helped me achieve that.

I was unable to find a Model Context Protocol (MCP) server implementation for Prometheus. I had a quiet weekend and so I’ve been writing one: prometheus-mcp-server.

I used the code from the MCP for gRPC Health Checking protocol that I wrote about previously as a guide.

I wrote a series of stdin and HTTP tests to have confidence that the service is working correctly but I had no MCP host.

I discovered that Visual Studio Code through its GitHub Copilot extension functions has a preview to use MCP servers i.e. function as an MCP host and access MCP servers.

Model Context Protocol (MCP) is “all the rage” these days.

I stumbled upon protoc-gen-go-mcp and think it’s an elegant application of two technologies: programmatically generating an MCP server from a gRPC protobuf.

I’m considering building an MCP server for Ackal but, thought I’d start with something simple: gRPC Health Checking protocol.

I was surprised to learn as I was doing this that there’s a new List (Add List method to gRPC Health service #143) added to grpc.health.v1.Health. My (Ackal) healthcheck server does not yet implement it (see later).

I’m building an emulator for Cloud Run. As I considered the solution, I assumed (more later) that I could implement Google’s gRPC interface for Cloud Run and use Envoy to proxy HTTP/REST requests to the gRPC service using Envoy’s gRPC-JSON transcoder.

Google calls this process Transcoding HTTP/JSON to gRPC which I think it a better description.

Google’s Cloud Run v2 (v1 is no longer published to the googleapis repo) service.proto includes the following Services definition for CreateService:

I have built Prometheus Exporters for multiple cloud platforms to track resources deployed across clouds:

• Prometheus Exporter for Azure
• Prometheus Exporter for crt.sh
• Prometheus Exporter for Fly.io
• Prometheus Exporter for GoatCounter
• Prometheus Exporter for Google Analytics
• Prometheus Exporter for Google Cloud
• Prometheus Exporter for Koyeb
• Prometheus Exporter for Linode
• Prometheus Exporter for PorkBun
• Prometheus Exporter for updown.io
• Prometheus Exporter for Vultr

Additionally, I’ve written two status service exporters:

• Prometheus Exporter for GCP Status
• Prometheus Exporter for Vultr Status

These exporters are all derived from an exemplar DigitalOcean Exporter written by metalmatze for which I maintain a fork.

I’m a little obsessed with creating Prometheus Exporters:

• Prometheus Exporter for Azure
• Prometheus Exporter for crt.sh
• Prometheus Exporter for Fly.io
• Prometheus Exporter for GoatCounter
• Prometheus Exporter for Google Cloud
• Prometheus Exporter for Koyeb
• Prometheus Exporter for Linode
• Prometheus Exporter for PorkBun
• Prometheus Exporter for updown.io
• Prometheus Exporter for Vultr

All of these were written to scratch an itch.

In the case of the cloud platform exporters (Azure, Fly, Google, Linode, Vultr etc.), it’s an overriding anxiety that I’ll leave resources deployed on these platforms and, running an exporter that ships alerts to Pushover and Gmail, provides me a support mechanism for me.

Obsessing on gRPC Firestore Listen somewhat but it’s also a good learning opportunity for me to write stuff in Rust. This doesn’t work against Google’s public endpoint (possibly for the same reason that gRPCurl doesn’t work either) but this does work against the Go server described in the other post.

I’m also documenting here because I always encounter challenges using TLS with Rust (and this documents 2 working ways to do this with gRPC) as well as references two interesting (rust) examples that use Google services.