Why Is Claude Ignoring Your MCP Prompts? A Troubleshooting Guide
Z
Zack Saadioui
8/11/2025
Here’s the thing about working with cutting-edge AI like Claude Code: it’s incredibly powerful, but sometimes it feels like it has a mind of its own. You craft what you think is the PERFECT prompt, you hit enter, &... nothing. Or, worse, you get a response that completely misses the point. It’s frustrating, right? Especially when you’re trying to leverage the awesome power of the Model Context Protocol (MCP) to connect Claude to your tools & automate your workflow.
If you’ve found yourself yelling at your screen, "Why is Claude ignoring my MCP prompts?!", you’re not alone. Turns out, there are a bunch of reasons why this might be happening, ranging from simple configuration screw-ups to some deep, subtle issues with how the AI manages its own context.
I’ve been in the trenches with this stuff, so I wanted to put together a real-deal guide on what’s actually going on when Claude Code seems to give your prompts the cold shoulder, & more importantly, how to fix it. This isn't just about theory; it's about practical steps you can take to get back to building cool stuff.
First Off, What's the Big Deal with MCP Anyway?
Before we dive into the problems, let's just quickly level-set on what MCP is & why it's a game-changer. At its core, Claude Code is a language model that’s great at, well, code. But on its own, it’s isolated. It can’t talk to your Jira board, it can’t check for errors in Sentry, & it can’t query your customer database.
That’s where the Model Context Protocol (MCP) comes in. It’s an open-source standard that acts as a bridge. By setting up or connecting to MCP servers, you give Claude Code access to your external tools, APIs, & data sources. Suddenly, you can ask it to do things like:
"Hey, grab the feature specs from Jira ticket ENG-4521 & write the boilerplate code for it."
"Check Sentry for any new errors related to the payment feature we just shipped."
"Pull the latest design system updates from Figma & refactor this component."
It’s how you go from a simple code generator to a true AI-powered engineering partner. But this bridge can be a bit wobbly if you don’t know its quirks.
The #1 Culprit: Your Context Window is a Mess
This is, honestly, the most common & misunderstood reason for prompts going sideways. We need to talk about "Context Engineering" & a nasty little problem called "Context Poisoning."
Think of Claude's "context window" as its short-term memory. It’s everything the AI is currently thinking about: the code you’ve been working on, the files you have open, the history of your conversation, & CRUCIALLY, any data piped in from your MCP servers.
Here’s the problem: if that memory gets cluttered or filled with bad information, the AI's performance tanks. It’s like trying to have a coherent conversation with someone who is simultaneously listening to three different podcasts & a news report. They’re going to miss things.
How does this "Context Poisoning" happen?
It happens when tainted or irrelevant data gets injected into the context window, usually via an MCP server. For example:
You’ve connected Claude to a public GitHub repository to pull issue data. If that repo has spammy or maliciously crafted issues, that junk is now in Claude’s head.
You’re using a tool to pull in blog comments for sentiment analysis, & those comments are full of irrelevant nonsense.
You’ve connected too many MCP servers at once, & they’re all feeding information into the context, creating a confusing mess.
When the context is poisoned, Claude might seem to "ignore" your prompt because it’s overwhelmed, confused by conflicting information, or its attention has been diverted by the tainted data.
How to Fix a Poisoned Context:
Nuke It From Orbit (The Easy Way): The quickest fix is often the best. Just run the
1
/clear
command. This wipes the slate clean, clearing the conversation history & context window. It's the "turn it off & on again" of Claude Code, & it works surprisingly often.
Practice Good "Context Hygiene": Be mindful of what you’re connecting Claude to. Before you hook up an MCP server that pulls from a public data source, consider the risk of tainted data. Can you trust the source? Is the data clean?
One Server at a Time: Especially when you’re debugging a problem, try to only connect one MCP server at a time. This helps isolate where the bad data might be coming from.
Check Your
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CLAUDE.md
: If you have a
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CLAUDE.md
file in your project for providing high-level instructions, make sure it’s concise & relevant. Overloading it with old or conflicting information can contribute to the clutter.
The Silent Killer: Configuration & Permission Errors
This category of problems is maddening because Claude won’t tell you what’s wrong. It will just fail silently. Your prompt for a tool won’t work, & you’ll get no error message, leaving you to wonder what you did wrong.
The issue is almost always a breakdown in the communication between Claude & the MCP server, usually due to authentication or permissions.
Common Configuration Traps:
Botched Authentication: Many cloud-based MCP servers use OAuth 2.0 to make sure you’re allowed to use them. When you add the server, it’s supposed to open a browser window for you to log in. If that process fails, or if your authentication token expires or gets revoked, the connection is dead. Claude can’t use the tool, so it just ignores any prompts for it.
Project Scope Approval: When you're on a team, you might use a
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.mcp.json
file in your project's root directory to share MCP configurations. This is super handy, but for security reasons, Claude will ALWAYS ask for your approval before using a server from that file. If you miss the prompt or deny it, Claude won't touch it. It’s easy to accidentally click "no" & then forget you did.
The Principle of Minimum Access: This is a core security concept that can bite you. Let's say you want Claude to fix a bug & create a pull request. To do that, it needs
1
read
&
1
write
access to the repository. If the token you’re using only grants
1
read
access, the first part of your prompt (reading the code) might work, but the second part (creating the PR) will fail without a peep.
How to Fix Configuration Issues:
Re-Authenticate: If you suspect an auth issue, the best bet is to revoke access & start over. Use the
1
/mcp
menu to find the option to "Clear authentication" for the server in question, then add it again, making sure to complete the login process in your browser.
Reset Project Approvals: If you think you might have accidentally denied access to a project-scoped server, you can reset your choice. Run the
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claude mcp reset-project-choices
command in your terminal. The next time you open the project, it will ask for approval again.
Check Your Permissions: Always ensure the credentials or tokens you're using have the EXACT permissions needed for the task you're asking Claude to perform. Don't assume. If it needs to write, give it write access. If it only needs to read, stick to that.
Confirm Tool Use: This is a great security habit anyway. By default, don’t give Claude blanket approval to use tools. Let it prompt you each time. This not only acts as a security check but also gives you a clear signal: if you don't get a prompt to approve a tool, it means Claude isn't even trying to use it, which points you back to a configuration or context problem.
It's Not You, It's Me: Technical Bugs & Limitations
Sometimes, the problem isn’t your prompt or your setup. It's a known bug or a limitation in Claude Code itself. This is the reality of working with rapidly evolving software. Two big ones stand out right now:
1. The "Stale Commands" Bug
You just built an awesome new custom command in your MCP server. You’re excited to use it. You fire up Claude, type
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/
... & it’s not there. What gives?
There’s a known issue where Claude Code doesn’t always pick up on new or changed commands dynamically. Technically, your MCP server is supposed to send a
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notifications/prompts/list_changed
message, which tells Claude to refresh its command list. But it doesn't always work. The new commands are there, but Claude's brain hasn't loaded them yet.
The Fix: The only surefire solution right now is the simplest one: restart Claude Code. Close the application completely & reopen it. This forces it to re-scan all connected MCP servers & load the latest set of commands. It’s annoying, but it works every time.
2. The Awkward Argument Handling Problem
This is a HUGE one that makes prompts feel like they’re being ignored. Many MCP commands need to take arguments, like a commit message or a task description. The problem is, Claude's argument handling is... well, basic.
No Multi-Word Arguments: You can’t just pass a sentence with spaces as an argument. For example,
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/commit "feat: add cool new button"
will fail. The system sees each word as a separate, invalid argument. The workaround is to use underscores, like
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/commit feat:_add_cool_new_button
. It's clunky & unnatural.
No Argument Discovery: There’s no easy way in the UI to see what arguments a command even accepts. You can’t tell if they’re required or optional, or what format they expect. This leads to a ton of trial & error, where you're essentially guessing at the right syntax, & every wrong guess feels like Claude is ignoring you.
The Fixes & Workarounds:
Embrace the Underscore: For now, when passing multi-word text, get used to replacing spaces with underscores. It’s a pain, but it’s the most common workaround.
Check the Server Code: If you have access to the MCP server's source code, that's the best place to see exactly what arguments a command expects.
Propose a Better Way: The community is aware of this. There's an active GitHub issue proposing solutions like supporting quoted strings for arguments & building an interactive UI for discovering them. Go add your voice to it!
The Paradigm Shift: You're Using "Tools," Not "Prompts"
This last one is less of a bug & more of a misunderstanding of the true power of MCP. Most people think of MCP as a way to give Claude "tools" it can call. But according to some of the top minds building with this tech, that's only scratching the surface. The real magic is in crafting "prompts" within your MCP server.
What’s the difference?
A Tool is a single, discrete action.
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load_data_set
is a tool.
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create_github_issue
is a tool.
A Prompt is a guided, agentic workflow. It’s a pre-packaged recipe that can chain multiple tool calls together, prime the AI with necessary context, & even suggest next steps.
For example, instead of manually calling tools to load data, analyze it, & then visualize it, you could create a single MCP prompt called
1
/perform_customer_churn_analysis
. When you run that, the prompt itself guides Claude through the entire multi-step process.
If you’re just trying to call individual tools with basic commands, you might be fighting the system. Claude might seem to be "ignoring" you because it lacks the higher-level context that a well-crafted prompt provides.
How to Shift to a Prompt-Based Workflow:
Build a "Capabilities" Prompt: The VERY first prompt you should build in any custom MCP server is one that explains what the server can do. Something like
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/my_server_capabilities
. This prompt should output a clear, structured list of all available prompts, tools, & resources. You run this once at the start of your session to load the "manual" directly into Claude's context window.
Compose Tools into Workflows: Think about your common tasks. Do you frequently have to look up a customer in your database, then check their recent support tickets, & then draft an email? That’s a perfect candidate for an MCP prompt. Turn that sequence of tool calls into a single, reusable AI developer workflow.
Guide the User (and the AI): Use prompts to create a guided experience. Your prompts can output suggestions for what to do next, keeping you (and the AI) in a state of flow.
This is a much more sophisticated way of working, & it’s where the real velocity gains are. It’s less about giving Claude a wrench & more about giving it a full set of IKEA instructions.
Drawing a Parallel: Building Smart Customer-Facing Assistants
It's pretty cool how this concept of guided, context-aware AI workflows isn't just for developers. It's the same principle behind creating genuinely helpful customer experiences. For years, businesses have been stuck with clunky, frustrating chatbots that feel like talking to a wall. They "ignore" your real questions because they are just simple, single-action tools.
But here’s the thing: modern platforms are changing that. This is where a solution like Arsturn comes into the picture. It allows a business to do for its customers what a good MCP server does for a developer. Instead of just having a dumb bot that recognizes a few keywords, you can build a no-code AI chatbot trained on your own data.
Think about it. You can feed it your entire knowledge base, your product documentation, your FAQs, & your past support conversations. The result is an AI assistant that doesn't just respond; it understands. It can guide a user through a complex troubleshooting process, answer nuanced questions about billing, & even help them choose the right product—all available 24/7. It's about building a conversational AI platform that creates a meaningful connection with your audience through personalized experiences. It’s the same paradigm shift: moving from simple, clunky tools to intelligent, guided workflows.
Tying It All Together
So, if you’re pulling your hair out because Claude Code is ignoring your MCP prompts, take a deep breath. It's probably one of these four things:
Your context window is a mess. Fix it with
1
/clear
& be more careful about your data sources.
There’s a silent configuration or permission error. Re-authenticate, check your project approvals, & make sure you have the right access levels.
You’ve hit a technical bug. Restart Claude to load new commands & use underscores for arguments until a better fix arrives.
You’re thinking in terms of "tools," not "prompts." Level up your MCP server by building guided workflows that give Claude the context it needs to shine.
Working with AI assistants requires a new way of thinking. It's part engineering, part teaching, & part debugging a very weird, very smart black box. The more you understand what's going on under the hood, the less mysterious & frustrating it becomes.
Hope this was helpful. Let me know what you think, & if you’ve found any other weird quirks or solutions, I’d love to hear about them. Happy coding