How to give Claude (or Cursor) access to your Rails app's activity logs

A developer built the EZLogs MCP server to give AI assistants like Claude and Cursor deterministic access to Rails app activity logs. The server exposes read-only tools that return structured, human-readable event data, preventing AI hallucinations by ensuring answers are based on real facts rather than pattern matching. The design deliberately avoids using language models for translation, relying instead on correlation and templates to produce consistent, traceable outputs.

Ask Claude this, today, with no setup: "What did user 4421 do in our app yesterday?" You will get an answer. It will be confident, specific, and completely made up. Claude has no access to your production database. So it does what a language model does when it has no facts: it pattern-matches what an answer should look like and hands you fiction in a calm voice. That is the whole problem. Not that the model is dumb. That it is answering a question about your data without your data. The Model Context Protocol fixes this, if you point it at the right source. This post is about what MCP is for a Rails dev who hasn't wired one up yet, why you'd want one over your app's activity log, and how I built the EZLogs MCP server so the answer is the boring true one instead of the confident fake one. MCP is a small open protocol from Anthropic. It lets an AI client Claude Desktop, Cursor, your internal copilot call out to a server you control and ask for data, mid-conversation, before it answers you. That's it. It is not a framework. It is not a model. It is a way for the model to say "hold on, let me go look" instead of guessing. A server exposes three things: The AI decides when to call them. You decide what they return. The protocol is just JSON-RPC over HTTP at a single endpoint. You could point an MCP server at your raw database. People do. It goes badly for the same reason raw logs go badly for humans: the model gets gid://app/Order/4421 , a pile of foreign keys, and a Sidekiq job class, and now it has to do the translation. So it guesses at the join, guesses at what the columns mean, and you are back to a confident fake answer, just one layer deeper. An activity log is already the translated layer. One row per user action, correlated across HTTP, background jobs, and database changes, with a human-readable name. "User 4421 tried to ship order 4421, address validation failed, the retry job ran three times and gave up." When the model reads that , it has nothing left to invent. The facts are already facts. So the activity log is the better MCP source precisely because the hard part, correlation and naming, was done before the model showed up. Here is the line I care about most, and the one I'd push back on hardest if you were evaluating any tool in this space. The translation in EZLogs has no model in it. The cards your team reads, and the data the MCP server returns, are produced by correlation plus templates. Same events in, same sentence out, every time. The action stream is folded into state with pure functions that never call an LLM and never write to the database, and every value carries the IDs of the specific events it came from. You can click any number back to its evidence. That means when your AI asks the EZLogs MCP server "what happened to order 4421," the rows it gets back are deterministic facts, not a second model's opinion. Your AI narrates them. Our side never narrates. We hand over structured data with citations; the model turns it into a sentence and spends its own credits doing it. This is the difference between "the AI made up an answer" and "the AI read the answer." A year into shipping AI features, that is the distinction CTOs are actually asking about. Where do the facts come from, and can I trace them. Six query-only tools. Every one of them reads. None of them writes back into your app, ever. That is a permanent design rule, not a current limitation: EZLogs holds no write credentials into your systems, so the blast radius of the whole thing is read-only. find actions and top lists are on the free tier. The rest are paid. MCP usage itself is unlimited on every paid tier, because the AI spends its own credits to narrate; we just deliver the rows. There are also read-only resources ezlogs://recent , ezlogs://actor/{id} , and friends and prebuilt prompts summarize day , investigate failure , incident report for the common questions. Two steps. Get events flowing, then connect your AI. Rails app the gem captures HTTP, Sidekiq, and ActiveRecord with no manual middleware : Gemfile gem 'ez logs agent' bundle install rails generate ez logs agent:install config/initializers/ez logs agent.rb EzLogsAgent.configure do |config| config.server url = "https://app.ezlogs.io" config.project token = "ezl your key here" end Next.js app , if that's your stack instead or as well, is npm install ezlogs-nextjs plus a small instrumentation.ts . Both agents emit the identical wire format, so the server treats them as one source. Then connect Claude or Cursor. For Cursor, add to ~/.cursor/mcp.json : { "mcpServers": { "ezlogs": { "url": "https://app.ezlogs.io/mcp", "headers": { "Authorization": "Bearer ezl your key here" } } } } For Claude Desktop on macOS it's one command, which backs up your existing config and merges in the EZLogs entry: curl -fsSL https://app.ezlogs.io/install/claude-desktop.sh | sh Quit Claude, reopen, and ask it "what happened yesterday?" This time it goes and looks. It isn't a metrics platform and it isn't an APM. It doesn't watch CPU or page you at 3am. Datadog watches your infrastructure; this explains the work your app did, in language a support person can read. It also isn't an AI tool that translates your logs. The AI is on your side of the connection, the one asking questions. The translation underneath is deterministic and the same with the AI turned off. If removing every model from the path would break the answer, the design would be wrong. It doesn't. There's a free tier, no card, and the MCP server is part of it. If you've got a Rails or Next.js app and an AI client you keep wanting to ask about production, point one at the other and see if the answer holds up. If you wire it up and the answer comes back wrong, or worse, comes back confidently fake, tell me. That's the one bug this whole thing exists to not have. Razvan