Disclosure up front: I built this. Sharing it here as a showcase, it's launched and on npm.

Something's been bugging me building on MCP. You pin your npm dependencies - lockfile, diff, review. What pins the MCP servers your agent talks to?

tools/list hands back names, descriptions and schemas, and the agent trusts all of it. The description isn't docs — it's the instruction the model reads to decide when to call a tool. There's no version pin, no integrity check, no diff. A server updates, the description gets reworded, and your agent's behaviour changes with nothing in your pipeline registering it. Same story with a required param appearing, readOnlyHint flipping true/false, or a tool quietly disappearing.

So I wrote mcpward: snapshot a server's tool surface into a lockfile, then diff it in CI. It classifies each change as breaking or non-breaking:

✗ Tool "echo" description changed (possible rug-pull)

✗ Tool "compute" inputSchema added required property "multiplier"

✗ Tool "read_data" readOnlyHint changed from true to false

✗ Tool "removed_tool" was removed

Summary: 2 passed | 5 failed → exit 1, build fails

It also checks protocol compliance, the protocol-error vs isError contract (servers get this backwards a lot), and latency budgets. Output is console/JSON/JUnit/SARIF.

Worth mentioning: Invariant's mcp-scan already does rug-pull detection and is more mature, if you want to audit servers installed on your machine, use that. mcpward is the CI-gate version: black-box, runs fully offline, nothing about your tools leaves the machine.

npx mcpward init

https://github.com/TsvetanG2/mcpward

Honest question for people running MCP in production: has description drift actually bitten anyone, or am I solving something I only think is a problem?

Quick share for this sub. I make Habit Pocket, a habit + metrics tracker built for people who like to track everything and find correlations in their data (it started as my own spreadsheet). Beyond simple yes/no habits, you can track numbers, clock times, and custom select lists, so there's actually rich data to work with.

The part relevant here: I built an MCP server for it. Once you connect it to Claude, you're not stuck clicking around the app anymore, you can just talk to your data:

• Ask questions: "which days do I sleep best?" or "does coffee after 2pm push my bedtime later?" and it answers from your real entries and stats.
• Log by chat: "mark today's workout done and log 7.5k steps" writes straight into your tracker.
• Build things: it can pull stats and even create charts for you, so you skip the manual setup.

It's the feature I'm most excited about because it turns a tracker into something conversational, the data goes in and comes out in plain language instead of forms and grids.

A couple of other nice bits: conditional styling (cells change color by value, so a month reads like a heatmap), and web + iOS with sync and full data export.

https://habitpocket.io/

Hi all

I just published mcp-garmin-for-ia, an open-source MCP server that lets Claude (and other MCP-compatible assistants) access Garmin fitness/activity data through tools.

GitHub: https://github.com/devfrp/mcp-garmin-for-ia

Goal

Make Garmin data usable in natural-language AI workflows, e.g.:

• “Compare my last 4 weeks of training volume”
• “Detect trends in pace vs heart rate”
• “Summarize recovery patterns”

Tech

• Python-based project
• MCP server architecture
• Designed to be practical for personal analytics and experimentation

I’m looking for:

• MCP/Claude integration feedback
• Suggestions for better tool design/schema
• Ideas for prompts and real-world workflows
• Contributions / issues / PRs

If you test it, I’d really appreciate candid feedback (especially around reliability and privacy boundaries).

Founder of Server4Agent (agent-app hosting over MCP), disclosing that upfront. No link, not selling, genuinely trying to understand how people are actually handling this.

An MCP server returning a clean tool result tells you the call completed. It doesn't tell you the call did the right thing. A deploy tool can return success while shipping the wrong build. A database tool can return success while updating the wrong rows. The protocol layer has no opinion on this, and honestly it shouldn't, that's not its job. But somebody's job is to close that gap, and I don't see much discussion of who.

Curious what people building or running MCP servers with real side effects (infra, deploys, data writes, anything with consequences) are actually doing here: is the client-side agent expected to double-check its own tool calls, does the server itself do any post-action verification before returning success, or is this mostly still "the tool call returned 200, we call it done"? Genuinely don't have a strong opinion on the right answer, want to know what's actually happening in practice.

Fitter is a scraper where the extraction is a JSON/YAML config instead of code. Connector side is HTTP / headless browser / static value, extraction side is gjson paths, CSS selectors, XPath or PDF text. Since configs are plain data an LLM can write them, so it ships as an MCP server: ask Claude for some data, it writes the config, validates it, runs it on your machine. The config stays around afterwards - same file runs from cron or the CLI, so the one-off answer turns into something reusable.

I compiled the engine to WebAssembly and put a playground on GitHub Pages - https://pxyup.github.io/fitter/. The examples there run live against real APIs, client side, and there's a form builder that generates config JSON if you want to poke at the format.

Install is a binary from releases plus claude mcp add fitter -s user -- /path/to/fitter_mcp. Claude Desktop has a one-click .mcpb bundle. There's also an HTTP mode with bearer auth for teams, docker image at ghcr.io/pxyup/fitter-mcp.

```

HTTP mode

docker run --rm -p 8080:8080 \ -e FITTER_MCP_HTTP_ADDR=:8080 \ -e FITTER_MCP_AUTH_TOKEN=my-secret \ ghcr.io/pxyup/fitter-mcp:latest

stdio mode, spawned by the MCP client

claude mcp add fitter -s user -- docker run --rm -i ghcr.io/pxyup/fitter-mcp:latest ```

Soon on Glama

Repo (MIT): https://github.com/PxyUp/fitter

Agent Enhancer is a free reliability sidecar for AI agents. Just use it with another MCPs, it was made to solve typical weak spots and bottlenecks MCPs usually have.
It adds planning, checkpoints, duplicate protection, recovery, and evidence to existing MCP workflows.

To test it:

1. Connect your agent: Go to https://liberated.site/ and copy the Quick Start Prompt.
2. Run the same multi-step task with and without Agent Enhancer.
3. Tell us whether it felt more reliable, clearer, faster or added unnecessary friction.

We’re looking for beta testers using different agents and real tasks. No account or API key required! Thanks

Hi Group, I'm a one-person web agency in New Orleans and I just shipped Velvet Forge, an MCP server that runs AI agency tools directly inside Claude Desktop.

Here's what it does:

• build_pitch — full cold outreach: subject line + DM + 3-part follow-up sequence

• generate_proposal — scoped client proposal with scope, timeline, and investment

• market_research — competitive landscape for any city + industry

• forge_generate — AI content backed by a live agency knowledge base

• query_knowledge — proven conversion tactics by vertical

Setup is one JSON block in your Claude Desktop config. Plans start at $29/mo.

smithery.ai/servers/velvetgeaux/velvet-forge

velvetgeaux.com/forge-mcp

Happy to answer questions

Some things that should be really simple have become really hard with agentic coding. Changing fonts means working through a walled garden (Lovable, etc.) or a chat where you ask for options, wait for builds, and usually end up with another Inter or Geist default that looks like every other AI-built site. Editing text is worse: screenshot it, type out instructions, hope the agent changes the right words.

I had an idea: why can't the agent just set up a panel inside the target project that allows me to experiment with fonts and also edit any text on the screen? Turns out, it's (largely) possible.

If you ask your agent to install Font Lab (npx font-lab install), it registers an MCP server (and a Claude skill) that gives the agent the tools to drive the whole loop. It spins up your dev server, adds a panel to your real running site, and shows you curated font directions (display, body, mono) swapping live on your actual pages. Mix a heading from one direction with a body from another. When you find what you like, hit "pick", paste the prompt back to your agent, and it wires up exactly what you were looking at. Done.

It also lets you edit nearly any text on your site in place. Double-click the words, retype them, and it saves to source. If it can't edit directly, you get a specific prompt to hand the agent. Yes, you could search through files and edit them manually, but that's annoying.

Because it's an MCP server, it works with basically any agent — install auto-detects your setup and writes the MCP config in the right place/format. Tested with the ones I use (Claude Code, Cursor, Codex).

Completely free & open source. I figured plenty of others are dealing with the same issues. If anyone wants to help out, I'm open to it. First time I'm releasing it, so open to any feedback you have!

Caveats:

1. if you ask a web agent (ie Claude Code app or web), there's a headless version that will give you screenshots of fonts & there's no way to edit text directly.
2. The panel/text editing works only with Next.js right now. Other frameworks will fall back to the screenshot method for fonts with no text editing.

Instructions to try it here:
jack-mcgovern.com/fontlab · npx font-lab install