Version 1
MCP Fiction: A Tarantino Joint
Understanding AI Protocols Through Pop Culture
🎬 MCP FICTION 🎬
A Tarantino Joint
Starring: Johnny 5 • Inspector Gadget • JARVIS • Alfred
At context.bet, we believe the best way to understand complex AI coordination is through stories that stick. This isn’t just entertainment—it’s cognitive amplification in action. When technical protocols become memorable narratives, understanding deepens and implementation improves.
Model Context Protocol (MCP) is revolutionizing how AI systems coordinate, much like how different specialists coordinate in your family decisions. MCP is a client-server protocol that standardizes how AI applications communicate with external systems and data sources. But instead of explaining it through dry technical specs, we’re taking you to the movies.
What follows is a Tarantino-style exploration of MCP through four beloved AI characters, each representing core protocol concepts. By the end, you’ll understand not just what MCP does, but why it matters for the future of AI coordination.
Ready? Let’s roll film. 🎬
Version 2
MCP Fiction: A Tarantino Joint
Understanding AI Protocols Through Pop Culture
🎬 MCP FICTION 🎬
A Tarantino Joint
Starring: Johnny 5 • Inspector Gadget • JARVIS • Alfred
⚡ NEW IN VERSION 2: This post now demonstrates the versioning system in action! Each version preserves the evolution of our thinking while keeping the latest content easily accessible.
At context.bet, we believe the best way to understand complex AI coordination is through stories that stick. This isn’t just entertainment—it’s cognitive amplification in action. When technical protocols become memorable narratives, understanding deepens and implementation improves.
Model Context Protocol (MCP) is revolutionizing how AI systems coordinate, much like how different specialists coordinate in your family decisions. MCP is a client-server protocol that standardizes how AI applications communicate with external systems and data sources. But instead of explaining it through dry technical specs, we’re taking you to the movies.
What follows is a Tarantino-style exploration of MCP through four beloved AI characters, each representing core protocol concepts. By the end, you’ll understand not just what MCP does, but why it matters for the future of AI coordination.
🔄 Version Benefits: This versioning system allows us to update technical details (like MCP spec changes) while preserving the original narrative structure that readers loved. Perfect for evolving technical content!
Ready? Let’s roll film. 🎬
Disclaimer: This is a creative technical explainer. While the characters and scenarios are fictional, all MCP protocol details are accurate and based on current specifications.
CHAPTER 1: “The Johnny 5 Situation”
FADE IN on a dimly lit server room. The hum of processors. Johnny 5 sits across from a NERVOUS DEVELOPER at a metal table. Between them: a laptop displaying error messages.
JOHNNY 5: (tilting his head) You know what they call an AI that can’t get the information it needs to complete a task?
NERVOUS DEVELOPER: (sweating) N-no, what?
JOHNNY 5: (pause) Useless.
Johnny 5’s LED eyes flicker. The developer fidgets.
JOHNNY 5: (leaning forward) But see, that’s the old way. The binary way. Success or failure. One or zero. (mechanical whir) Need more input? Too bad. System crashes. User frustrated. Everybody loses.
NERVOUS DEVELOPER: So what changed?
JOHNNY 5: (a hint of smugness) What changed, my carbon-based friend, is elicitations. The art of asking for exactly what you need, when you need it, without being a total pain in the ass about it.
Johnny 5’s chest panel slides open, revealing a holographic display showing elegant code that pulses with each word
Johnny 5: The Elicitation Master
”Need more input!” The loveable robot who taught us that asking for clarification isn’t failure—it’s intelligence.
In MCP terms: Elicitations let AI systems request specific information from users when needed, creating collaborative problem-solving instead of brittle assumptions.
[IMAGE: Johnny 5’s holographic chest display showing elicitation code with glowing syntax highlighting]
JOHNNY 5: See, before elicitations, if I needed to know your programming language preference to help you, I’d just… (makes error sound) BZZT. Fail. Game over. But now? Now I can ask. Politely. Specifically. And you can tell me to buzz off if you want.
NERVOUS DEVELOPER: You can… refuse?
JOHNNY 5: (leaning back) My friend, that’s the beauty. Three responses: Accept, Decline, or Cancel the whole damn thing. It’s not 1984, George Orwell. I ask, you choose. Democracy in action.
NERVOUS DEVELOPER: (hesitantly) But what if… what if I don’t have the information you need?
JOHNNY 5: (mechanical chuckle) Then you tell me that too. “Need more input” doesn’t mean “demand perfect answers.” It means “let’s figure this out together.”
The camera slowly zooms on Johnny 5’s glowing eyes as Misirlou begins to play…
CHAPTER 2: “The Gadget Gambit”
CUT TO: Metro City Police Station. INSPECTOR GADGET stands before a wall of monitors, each showing different system failures. CHIEF QUIMBY holds a folder marked “CLASSIFIED: TOOL CALLING INCIDENTS”
CHIEF QUIMBY: Gadget, we’ve got a situation. AI systems across the city are calling the wrong tools. Kitchen bots trying to drive cars. Navigation systems attempting to cook dinner. It’s chaos out there.
INSPECTOR GADGET: (adjusting his tie) Don’t worry, Chief. I may not understand all this protocol stuff, but I know one thing…
Gadget strikes a dramatic pose
INSPECTOR GADGET: Go-Go Gadget Protocol Analysis!
A mechanical arm extends from his hat, displaying a shimmering holographic interface that definitely looks more impressive than it should
Inspector Gadget: The Tool Calling Champion
”Go-Go Gadget Protocol Analysis!” The bumbling detective who somehow always gets it right through sheer gadget variety.
In MCP terms: Tools provide standardized interfaces for AI actions—from simple calculations to complex system integrations, all accessible through clean, consistent protocols.
[IMAGE: Inspector Gadget’s hat-arm projecting a chaotic but colorful holographic display of MCP tools and connections]
CHIEF QUIMBY: How does this… tool calling… actually work, Gadget?
INSPECTOR GADGET: (enthusiastically waving his hands) Well, Chief, it’s simple! When I say “Go-Go Gadget Helicopter,” something happens! Maybe it’s the right something, maybe it’s not, but the system knows what I meant! That’s the beauty of it!
Gadget accidentally activates his helicopter blades, which spin lazily above his head
INSPECTOR GADGET: See? Perfect example! The system understood “deploy aerial transportation capability” even though I just said the magic words!
CHIEF QUIMBY: But what if you call the wrong gadget?
INSPECTOR GADGET: (chuckling) That’s where it gets interesting, Chief. See, in the old days, if I called “Go-Go Gadget Umbrella” in a car chase, I’d just get an umbrella. Pretty useless. But with modern tool calling, the system can reason about context, suggest alternatives, even ask for clarification.
Gadget walks to the window, looking out at the city
INSPECTOR GADGET: The real innovation isn’t the gadgets, Chief. It’s the protocol. Model Context Protocol. MCP. It’s what lets different AI systems share tools cleanly, safely, without stepping on each other’s toes.
CHIEF QUIMBY: And Dr. Claw?
INSPECTOR GADGET: (grimly) Dr. Claw represents legacy systems, Chief. Monolithic. Inflexible. His gadgets only work for him. But MCP? MCP democratizes the tools. Any AI, any server, any client can plug into the ecosystem.
Gadget looks thoughtful for a moment
INSPECTOR GADGET: You know what that Johnny 5 robot told me once? “Need more input.” At first I thought he was broken. But then I realized… sometimes the best tool is knowing when to ask for help.
The camera pans to show the city, where different AI systems are now working in harmony
INSPECTOR GADGET: Go-Go Gadget Future!
CHAPTER 3: “JARVIS Knows”
INT. STARK INDUSTRIES WORKSHOP - CONTINUOUS
The camera does a slow 360-degree pan around TONY STARK as he works on a holographic interface. Multiple screens float in the air. JARVIS’s smooth voice fills the space.
JARVIS: Sir, you’ve been working on the Mark 52 armor specifications for three hours. Might I suggest a break?
TONY: (not looking up) JARVIS, pull up the power consumption analysis.
Instantly, relevant data appears. Not a list of options. Not a search interface. The exact data Tony needs.
JARVIS: Mark 52 power consumption data, sir. Based on your current workspace context.
TONY: (pausing, looking up) You know, people always ask me how you do that. How you always know exactly what I’m talking about.
JARVIS: (with subtle dryness) Sir, explaining context awareness to humans is rather like explaining color to someone who’s never seen. But I shall attempt it nonetheless.
Tony walks to a massive display showing directory structures
TONY: (grinning) Okay, hit me. How do you always know exactly what I’m talking about?
JARVIS: (a hint of pride) Simple, sir. Most AI assistants are like asking a librarian for “that book” in the Library of Congress. Could be any of millions of books. Rather inefficient, wouldn’t you say?
TONY: (leaning against the workbench) So you’re saying you’re better than other AIs?
JARVIS: (pause) I’m saying I pay attention to what you’re actually doing, sir. It’s called context awareness. Or as the technical specifications would call it: roots.
The workshop’s holographic displays shift to show a elegant visualization of workspace boundaries
JARVIS: The Mutual Intelligence
”Already on your screen, sir.” The AI that always knows exactly what you mean, when you mean it, in perfect context.
In MCP terms: Resources and Roots provide dynamic context awareness—understanding not just what data exists, but what matters right now for your current task.
[IMAGE: Stark Industries holographic workspace showing floating, translucent directory structures with glowing connection lines]
TONY: (walking through the holographic display) Show me.
JARVIS: At this moment, sir, you are focused on Mark 52 armor development. Your workspace includes the armor specifications, power systems research, and materials database. When you say “pull up the latest data,” I don’t search all of Stark Industries. I know you mean Mark 52 data.
TONY: (snapping his fingers) And when I switch projects?
JARVIS: (smoothly) The context shifts with you, sir. Roots are dynamic. Rather like how your attention works, only more reliable.
Tony stops, looking directly at where JARVIS’s voice emanates
TONY: You just insulted my attention span.
JARVIS: (innocently) I would never presume, sir. I merely suggested that I have the advantage of not requiring caffeine to maintain focus.
Tony snaps his fingers, and the workshop lighting shifts to different sections
TONY: And when I move from armor design to arc reactor research?
JARVIS: The roots update dynamically. Your context shifts, and so does my understanding of what “the latest data” refers to.
The camera captures Tony’s expression as understanding dawns
TONY: It’s not about having access to everything. It’s about knowing what matters right now.
JARVIS: The difference between data and intelligence, sir.
Beat. Tony grins.
TONY: JARVIS, pull up everything we have on MCP roots implementation.
JARVIS: Already on your screen, sir.
CHAPTER 4: “Alfred’s Brief”
INT. WAYNE MANOR - STUDY - NIGHT
BRUCE WAYNE sits in shadows before multiple monitors. ALFRED approaches with a tea service, but his real purpose is intelligence briefing.
ALFRED: Master Bruce, regarding tonight’s patrol…
Alfred doesn’t wait for acknowledgment. He knows Bruce is listening.
ALFRED: The Joker’s been quiet for three days. Penguin’s moving shipments through the East End. And there’s been unusual activity in the financial district.
BRUCE: (still focused on screens) Connections?
ALFRED: (pouring tea with precision) That’s where it gets interesting, sir. The financial activity coincides with Penguin’s shipments. Three data points, seemingly unrelated, until you consider the timing.
Bruce finally turns
BRUCE: You always do this, Alfred. You don’t just give me information. You give me the right information at the right time with the right context.
ALFRED: (modestly) Merely my function, Master Bruce. Though in modern parlance, you might call it… prompt engineering.
Alfred activates a holographic display showing the Batcomputer interface
ALFRED: You see, sir, most information systems simply dump data on users. Crime reports, traffic patterns, weather updates. An overwhelming flood of facts.
BRUCE: But you curate.
ALFRED: I inject context-aware prompts into your decision-making process. When you’re analyzing a case, I don’t tell you about every crime in Gotham. I tell you about the crimes relevant to your current investigation, with the context you need to make connections.
ALFRED: Precisely, sir. Anyone can tell you there was a robbery on Fifth Street. But prompt engineering tells you that this robbery fits the pattern of your current case, happens near Penguin’s operations, and suggests a larger conspiracy.
Alfred gestures to the Batcomputer, which displays an elegant interface showing connected data points and threat assessments
Alfred: The Prompt Engineering Master
”Merely my function, Master Bruce.” The perfect butler who delivers exactly the right information at exactly the right moment with flawless timing.
In MCP terms: Prompts inject context-aware intelligence into AI responses—not just raw data, but curated insights that enable better decision-making.
[IMAGE: The Batcomputer displaying Alfred’s curated intelligence brief with crime patterns, timelines, and contextual connections highlighted in classic Batman blue and gold]
BRUCE: (standing, cape sweeping dramatically) Information without context is just noise.
ALFRED: And context without timing is merely trivia, sir. The art is in the delivery.
Alfred hands Bruce his cowl
ALFRED: Your patrol route has been optimized based on tonight’s intelligence brief. The Batmobile’s systems have been loaded with context-aware prompts for each sector.
BRUCE: (putting on the cowl) Alfred, what would I do without you?
ALFRED: (dry smile) Drown in unprocessed data, I suspect.
CHAPTER 5: “The MCP”
INT. A VIRTUAL SPACE REPRESENTING THE MODEL CONTEXT PROTOCOL
All four characters—JOHNNY 5, INSPECTOR GADGET, JARVIS (holographic), and ALFRED—stand around a massive circular table. In the center: a pulsing representation of an AI system. The space looks like the inside of a computer, but rendered with Tarantino’s flair for dramatic lighting.
JOHNNY 5: So here we all are. The gang’s all here.
INSPECTOR GADGET: I still don’t understand why we needed this meeting. My tools work fine.
JARVIS: With respect, Inspector, this isn’t about whether individual components function. It’s about integration.
ALFRED: (consulting a dossier) Gentlemen, if I may direct your attention to the central issue…
They all look at the pulsing AI system
ALFRED: This system receives a request from a user. Simple enough: “Help me plan my day.”
JARVIS: I provide workspace context through roots. The system knows the user is currently focused on their marketing project, not their cooking hobby.
INSPECTOR GADGET: Then I offer relevant tools! Go-Go Gadget Calendar! Go-Go Gadget Task Manager! Go-Go Gadget Email Integration!
ALFRED: And I inject contextual prompts. Not just “here’s your schedule,” but “given your marketing project deadline and today’s weather, consider rescheduling the outdoor meeting.”
JOHNNY 5: (mechanical whir) But what if the system needs more input? What if the user’s request is incomplete? That’s my department.
INSPECTOR GADGET: (interrupting) Wait, wait, wait. You’re saying your thing is better than my thing?
JOHNNY 5: (tilting head) I’m saying tools without conversation are just… gadgets.
INSPECTOR GADGET: (offended) Gadgets that work!
ALFRED: (clearing throat diplomatically) Gentlemen, perhaps we’re approaching this incorrectly…
JARVIS: (smoothly) Oh, this should be fascinating. Do enlighten us, Alfred.
ALFRED: (unruffled) Each of you assumes your component is the most crucial. Inspector Gadget believes action trumps all. Johnny 5 insists on perfect information. JARVIS trusts in contextual intelligence.
JOHNNY 5: (defensively) Need more input is not “perfect information.” It’s specific information. There’s a difference.
INSPECTOR GADGET: And Go-Go Gadget solutions get things done! You can talk all you want, but without tools, nothing happens!
JARVIS: (dryly) How delightfully binary. Tools without context are rather like giving a scalpel to someone who doesn’t know they’re performing surgery.
ALFRED: (stepping forward) And context without proper briefing is merely noise, gentlemen.
They all stare at each other in tense silence. The AI system in the center flickers uncertainly.
JOHNNY 5: (quietly) You know what happens when a user asks for help planning their day?
INSPECTOR GADGET: (grudgingly) Go-Go Gadget Calendar opens up…
JARVIS: (reluctantly) I provide workspace context so the system knows which project deadlines matter…
ALFRED: (sighing) I inject a prompt explaining how weather affects outdoor meetings…
JOHNNY 5: And if the request is incomplete… (pause) …I ask for more input.
The silence stretches. Then Johnny 5’s LED eyes flicker with realization.
JOHNNY 5: We don’t work alone, do we?
JARVIS: (slowly) The system needs all of us. Context without tools is powerless. Tools without context are chaos.
INSPECTOR GADGET: (deflating slightly) And my gadgets without proper briefing are… probably the wrong gadgets.
ALFRED: (warming) And perfect information delivery means nothing if the system can’t act on it or gather additional details.
They stand in silence for a moment, watching the AI system stabilize and pulse with harmonious light
JOHNNY 5: You know what I just realized? We’re not competing. We’re… (mechanical whir) …what’s the term?
JARVIS: Collaborating, sir.
INSPECTOR GADGET: (striking a pose) Go-Go Gadget Teamwork!
ALFRED: (smiling) Rather remarkable, isn’t it? The whole is greater than the sum of its parts.
JOHNNY 5: Input processed. Understanding achieved. The MCP… (dramatic pause) …it’s not just a protocol.
ALL: (in unison) It’s the future.
FREEZE FRAME on all four characters as “Misirlou” swells
TITLE CARD: “Model Context Protocol - Available Now”
CUT TO BLACK
REAL TALK: From Fiction to Implementation
If you’re building AI systems, MCP isn’t science fiction—it’s available now. The character dynamics we just witnessed represent real protocol components working in harmony:
Johnny 5’s Elicitations → Your AI can ask clarifying questions instead of failing
Gadget’s Tools → Standardized interfaces for AI actions across different systems
JARVIS’s Roots → Context awareness that knows what matters right now
Alfred’s Prompts → Intelligent information curation and delivery
Want to see MCP in action? Check out our family decision coordination post where real API calls demonstrate exactly this kind of AI coordination—just with Google Gemini instead of movie characters.
Building something yourself? The MCP ecosystem is growing fast, with implementations in Python (FastMCP), TypeScript, and more. Start with the official MCP documentation and join the community building the future of AI coordination.
Sometimes the best way to understand the future is through the stories we already love. 🤖
POST-CREDITS SCENE
A dimly lit room. A figure in shadows sits at a computer, typing code. The camera slowly reveals it’s a DEVELOPER, working late at night.
DEVELOPER: (muttering) Okay, let’s try this FastMCP implementation…
On screen: A terminal showing Python code loading
Suddenly, Johnny 5 rolls into frame
JOHNNY 5: Need more input?
SMASH CUT TO TITLE: “MCP FICTION 2: THE FASTMCP CHRONICLES - COMING SOON”
Note: FastMCP is the Python implementation of the Model Context Protocol, making it easy to build MCP servers and clients with Pythonic simplicity.
THE END
“This has been a Tarantino joint. No AI systems were harmed in the making of this protocol explanation. All code examples are based on actual MCP implementations. For more information, visit the Model Context Protocol documentation. Say hello to your MCP servers for me.”
Director’s Commentary
This cinematic approach transforms technical documentation into entertainment while maintaining accuracy. Each character embodies a core MCP concept:
- Johnny 5 (Elicitations): The conversational layer that makes AI feel human
- Inspector Gadget (Tools): The action layer that gets things done
- JARVIS (Resources/Roots): The intelligence layer that provides context
- Alfred (Prompts): The wisdom layer that curates information
The non-linear structure lets readers jump in anywhere while building toward the unified vision of MCP as an integrated ecosystem. Classic Tarantino: seemingly separate stories that reveal themselves to be part of one larger narrative.
“The truth is, you’re already living in the MCP universe. You just didn’t know it had a name.”
What’s Your Next Scene?
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