Getting Pieces to Remember Stuff in VS Code Copilot (When It Doesn't Break)

So Model Context Protocol is Anthropic's latest attempt to solve the "why doesn't my AI remember anything" problem. Instead of each AI tool forgetting you exist the moment you close the tab, MCP lets them actually share context.

The architecture sounds simple: VS Code talks to MCP servers like Pieces, servers expose tools, Copilot calls those tools. Basically APIs for AI context. Works great in demos. Crashes in production.

How This Shit Actually Works

So you actually get Pieces, VS Code, and GitHub Copilot talking through MCP:

Pieces as the Memory Hoarder

Pieces runs locally and screenshots literally everything you do. Code snippets, Stack Overflow tabs, that Slack conversation where Sarah explained the API auth flow. It's basically surveillance software you installed voluntarily. The Long-Term Memory system OCRs your screen constantly and stuffs it in a database.

VS Code as the Middleman

VS Code 1.102+ has built-in MCP support that supposedly "just works." It's supposed to route requests between Copilot and your MCP servers. Usually fails with connection timeouts.

Copilot as the Consumer

GitHub Copilot's agent mode can theoretically call MCP tools. When it works, you can ask "what was that OAuth bug from last month?" and get actual answers. When it doesn't work, you get "I don't have access to that information."

The Information Flow (When Everything Doesn't Explode)

1. Pieces Hoards Everything: It's constantly watching your screen, grabbing contextual information from browsers, IDEs, Slack, whatever. Privacy advocates hate this one weird trick.

2. MCP Server Exposure: Pieces exposes this data through standardized MCP tools like ask_pieces_ltm. Think of it as an API, but for your entire digital life.

3. VS Code Routes Requests: When you ask Copilot something, VS Code figures out which MCP servers might help and routes the request accordingly.

4. Copilot Gets Smarter: Instead of generating code based on just your current file, Copilot can pull from your entire development history. It knows about that authentication bug you fixed last month.

The whole point? Solving that thing where developers spend half their time trying to remember what the hell they did yesterday. There's actually research on this duplicative effort bullshit, but you don't need a report to know it sucks.

Reality Check: Why This Matters

Before MCP, getting AI tools to share context was like trying to get anyone to update documentation after a sprint - technically possible, never happens. Now there's a standardized protocol for this mess.

Does it work perfectly? Hell no. But when it does work, you can ask Copilot "how did I handle rate limiting in that Express app?" and it actually knows because Pieces remembers the Stack Overflow thread you were reading three weeks ago.

The MCP ecosystem is growing fast, which means more tools will support this. Eventually. Maybe. If we're lucky.

When you finally get it configured, VS Code will show your MCP servers in the Copilot tools list, assuming everything didn't crash during startup. The VS Code MCP documentation has screenshots if you want to see what success looks like.

Time for the actual setup. Three attempts minimum, budget a full afternoon, and clear your schedule for debugging. The error messages you're about to see:

• ECONNREFUSED localhost:39300
• Server did not respond to initialization
• Tool invocation failed: timeout

These will become more familiar than your own name.

What You Need (And What Will Break)

Here's what you actually need, not the marketing bullshit:

• VS Code 1.102+ with the GitHub Copilot extension - and make sure it's actually activated, not just installed
• PiecesOS running locally - download it here and pray it doesn't crash on startup
• A GitHub Copilot subscription that actually works (check your billing page because GitHub loves to silently fail payments)
• Actual system permissions - macOS will ask for screen recording access and you HAVE to grant it or nothing works

macOS Sonoma 14.6.1 specific gotcha that cost me two hours: Pieces stops capturing after OS updates. System Settings → Privacy & Security → Screen Recording → check PiecesOS. Apple resets this permission silently. Learned this at 11pm on a deadline.

Step 1: Getting PiecesOS Not to Crash

First, install PiecesOS and watch it immediately ask for a dozen permissions. Grant them all or nothing will work.

The Reality: PiecesOS will probably crash on first launch. Check Activity Monitor (macOS) or Task Manager (Windows) to see if it's actually running. The system tray icon lies sometimes.

Enable Long-Term Memory: Find the PiecesOS icon (if it exists) and click "Enable Long-Term Memory Engine." This takes 15-20 minutes on a good day and might fail silently. You'll know it worked if it starts chewing through your RAM like it's going out of style.

Get the MCP Endpoint: This is where it gets fun. The endpoint is supposed to be http://localhost:39300/model_context_protocol/2024-11-05/sse but that port changes randomly. Check the PiecesOS logs to find the actual port. On Windows, it's usually in %APPDATA%\com.pieces.os\logs.

Common Failure: ECONNREFUSED 127.0.0.1:39300 means the port is wrong or PiecesOS died again. I've seen it randomly switch to port 39301 after updates. Restart everything and pray.

The Long-Term Memory settings are buried in the PiecesOS menu system. When you finally find them, they'll look like standard toggle switches, but half the time the toggle doesn't reflect the actual state of the service.

Step 2: Configuring VS Code (Where Things Get Stupid)

VS Code's MCP support is newer than your last failed deployment, so expect bugs.

Workspace Configuration (do this first):
Create .vscode/mcp.json in your project:

{
  "servers": {
    "pieces": {
      "type": "sse",
      "url": "http://localhost:39300/model_context_protocol/2024-11-05/sse"
    }
  }
}

When this breaks (and it will): Check the VS Code MCP logs via View → Output → Model Context Protocol. You'll see error messages like Failed to connect to SSE endpoint or Server did not respond to initialization.

Nuclear option: Cmd+Shift+P → "MCP: Add Server" and configure manually. Pick "HTTP (sse)" and paste the endpoint. VS Code will probably crash. This is expected. Restart and try again.

Debug mode: Add "debug": true to your MCP config. Enables verbose logging that shows exactly why the connection dies. Found three different timeout issues this way.

The VS Code MCP configuration UI will show server status indicators - green means connected, red means fucked, yellow means "it might work sometimes."

Step 3: Copilot Agent Mode (The Final Boss)

GitHub Copilot's agent mode is where the magic happens, assuming your computer hasn't exploded yet.

1. Open Copilot Chat: Cmd+Ctrl+I (macOS) or Ctrl+Alt+I (Windows). If nothing happens, Copilot crashed. Restart VS Code.

2. Switch to Agent Mode: Look for a dropdown that says "Ask" and change it to "Agent." If you don't see this option, your Copilot subscription is fucked or you're using an old version.

3. Check MCP Tools: Click the "Tools" button. If Pieces tools aren't listed, go back to step 1 because your MCP connection is broken.

4. Test It: Ask something like "What was I working on yesterday?" If it works, congratulations. If it says "I don't have access to that information," your setup is broken.

Common failures:

• Tool invocation failed: Connection timeout - Pieces crashed again
• No MCP tools available - Your MCP server isn't actually connected
• Copilot just ignores MCP entirely - This is a known issue with no ETA on a fix

When Everything Goes Wrong (Debugging Hell)

MCP Server Won't Connect:

• Check if PiecesOS is actually running (ps aux | grep pieces on macOS/Linux)
• Verify the port with netstat -an | grep 39300
• Try a different port in your config
• Restart everything in this order: PiecesOS, VS Code, your computer, your life

Copilot Can't See Pieces:

• Make sure you're in Agent mode, not Ask mode
• Check the MCP output logs for connection errors
• Try disabling and re-enabling the GitHub Copilot extension
• Clear VS Code's extension host cache by running "Developer: Restart Extension Host"

Performance is Shit:

• Pieces' Long-Term Memory is a resource hog. It's constantly OCR-ing your screen and will max out your CPU
• On older machines, disable LTM capture for apps you don't need
• The context database grows forever and gets slow. Clear it periodically or your queries will timeout

The Nuclear Reset:
When all else fails (and it will):

1. Quit PiecesOS completely
2. Delete ~/.pieces directory (this nukes all your stored context)
3. Uninstall and reinstall PiecesOS
4. Remove all MCP config from VS Code and start over
5. Consider switching to a different career

The whole point is making AI remember context across sessions. When it works, you can ask Copilot about code you wrote weeks ago. When it doesn't work, you'll spend more time debugging the setup than actually coding.

The GitHub Copilot agent interface shows available tools in a dropdown. When MCP is working, you'll see Pieces tools listed there. When it's broken, you'll see an empty list and a lot of confusion.

Success Stories (They Do Exist)

After 4 hours and two complete reinstalls, the magic moment:

• Asked "How did I fix that CORS issue last month?" - got the exact MDN documentation page I was reading
• "Show me that authentication pattern from the other project" - pulled actual code from Pieces' memory
• "What was that Stack Overflow answer about rate limiting?" - referenced the specific thread from three weeks ago

Works great until your next system restart. Or when the client is watching. Demo gods demand sacrifice.

Enterprise MCP:

When Management Gets Involved

MCP working on your laptop? Perfect. Now management wants 200 developers using it by Q 3. Guess who just became the company's MCP expert? You did. Congratulations, your weekends are gone.

VS Code settings management looks clean in documentation.

Corporate reality involves group policies that lock down localhost connections and IT departments that banned Chrome because "security."

Corporate IT Will Make Your Life Hell

Centralized Management:

Microsoft claims you can manage MCP servers centrally through group policies.

Your IT department will spend three months "evaluating" this, then lock everything down so tight that MCP can't connect to localhost.

Configuration Hell: You'll craft a perfect mcp.json config.

Works great on your machine. IT pushes it out and everything breaks because:

• Corporate firewalls block localhost ports (yes, really)

• McAfee quarantines PiecesOS as malware

• Group policies prevent network connections

• Screen recording permissions disabled globally

Security Theater: MCP servers execute code, so Info

Sec loses their minds.

Submitted the Pieces security review in March. It's now September. They want to "assess the binary for malicious code" but can't explain their assessment process. Meanwhile, we're still using Jenkins from 2018.

Corporate security teams love GitHub Copilot enterprise policies because they give the illusion of control.

MCP servers make them break out in cold sweats because they represent uncontrolled code execution.

Performance at Scale (Spoiler: It Doesn't)

Shared Server Fantasy:

The docs suggest Pieces server mode for teams.

Pieces doesn't actually support this properly yet. Shared databases become slow, one person's garbage context pollutes everyone's results, and network latency makes everything worse.

Tool Limit Hell: Copilot craps out around 128 tools, give or take.

Hit that limit and Copilot randomly ignores tools without telling you why.

Database Growth: LTM databases grow forever.

After six months, queries timeout, SSDs fill up, everything slows to a crawl. No cleanup tools exist.

Multi-Server Architecture (Complexity Hell)

Multiple Servers: Deploy multiple MCP servers and watch them fight:

• Server A times out, Server B crashes, the whole connection dies

• Copilot can't figure out which server does what

• Tool discovery becomes random

Team Knowledge Fantasy:

Build an MCP server for Confluence? Confluence's API is rate-limited, search results suck, and IT blocks it anyway.

DevOps Integration (More Problems)

CI/CD Integration: Build logs contain secrets, your CI system blocks external connections, and the MCP server crashes every deployment.

Code Review Integration:

Sounds great until it surfaces every nitpicky comment from your team's perfectionist reviewer and GitHub rate-limits kill it during crunch time.

Monitoring and Maintenance (Your New Full-Time Job)

Debugging Production Issues: When MCP breaks in production (and it will), you'll be staring at logs like:

[2025-09-05 14:32:12] ERROR:

 Server connection failed: ECONNREFUSED
[2025-09-05 14:32:13] INFO:

 Retrying connection...
[2025-09-05 14:32:14] ERROR:

 Server connection failed: ECONNREFUSED

These logs tell you nothing useful.

Is PiecesOS crashed? Is the port changed? Is there a network issue? Good fucking luck figuring it out.

Monitoring Hell: Track response times (always degrading), database sizes (always growing), and productivity metrics (always questioned by management).

Update Cycle:

VS Code updates break MCP, Pieces

OS updates change APIs, Copilot updates change tool invocation. You'll spend more time fixing than anyone spends benefiting.

VS Code's development mode debugging helps, but only if you can decipher the cryptic error messages and trace execution through multiple layers of MCP protocol abstraction.

The Reality Check

After six months of enterprise MCP deployment, you'll realize:

1. Most developers use only basic Copilot features and ignore MCP entirely

2. The 10% who use it spend more time troubleshooting than benefiting

3. Your help desk is flooded with "MCP stopped working" tickets

4. Management asks for ROI metrics you can't possibly measure

5. You become the single point of failure for everyone's AI productivity

What Actually Works at Scale

Skip the fancy MCP enterprise architecture.

Instead:

• **Use Git

Hub Copilot's built-in workspace context**

• it's reliable and requires zero configuration

• Write better documentation and put it in your repositories where Copilot can find it

• Standardize on simple, well-documented patterns instead of trying to capture every possible context

• Focus on code quality rather than AI-powered productivity theater

Save yourself the pain.

The promise of enterprise MCP is beautiful. The reality is debugging distributed systems that solve problems better documentation practices would fix more reliably.

But if you really want to go down this path, budget 2-3 full-time engineers just to maintain the MCP infrastructure. And prepare to become the company expert on SSE connection debugging and VS Code extension host crashes.

The GitHub enterprise architecture documentation makes everything look clean and simple. Reality is messier

• expect to spend most of your time troubleshooting connection issues rather than leveraging AI capabilities.