Glossary & Terminology
🔧 Core Protocol Terms
MCP
Model Context Protocol – Standard interface and schema for representing, verifying, and injecting contextual information into LLMs and intelligent agents.
MCP3
Third-generation protocol unifying context handling with Web3 primitives, enabling LLM/agent consumption, zk-proofs, and privacy-aware context orchestration.
MCO
Machine Context Object – Signed, structured, and optionally encrypted payload representing verifiable context for a specific subject (user or agent).
Context
Collection of user or agent-related attributes (identity, activity, state, access rights) that influence model behavior.
Scope
Permission label specifying which part of the context can be disclosed or used (e.g., read.profile
, read.dao
).
Subject
The identity (typically a DID or Ethereum address) for whom the MCO is created.
Prompt Augmentation
Process of inserting structured or embedded context into a model prompt to ground the LLM's behavior and reasoning.
🛡️ Security & Identity
EIP-712
Ethereum standard for signing typed structured data. Used to authenticate MCOs.
JWS
JSON Web Signature – Alternative signature format for backend implementations.
DID
Decentralized Identifier – Global standard for self-sovereign identity.
ZK Proof
Zero-Knowledge Proof – Prove something is true without revealing the underlying data.
Semaphore
ZK protocol for anonymous signaling. Used in proof-of-humanity and reputation-preserving settings.
RLN
Rate Limiting Nullifier – ZK-based rate limiting tool to prevent abuse in anonymous systems.
🔄 Data & Execution
Timestamp
Unix time indicating when the MCO was created. Used for expiration and freshness checks.
Expires_in
Optional TTL (time-to-live) in seconds, after which an MCO is invalid.
Signer
Wallet or key that signs a context object. Can be user or delegated bot.
Delegated Signer
Scoped, revocable signing key issued by a user to another entity (e.g., API key).
Merkle Tree
Tree of hashes for efficient and secure verification of data integrity. Used for batched attestations.
🤖 LLM Integration
Agent
AI component (usually LLM-based) using contextual information to take actions.
System Prompt
Prompt provided to the LLM to define persona, goals, or constraints. Often where context is injected.
Function Calling
Allows LLMs to call external tools/functions, enhanced by MCP3 context injection.
Context Injection
Embedding signed/structured context into an LLM prompt.
📦 Storage & Infrastructure
IPFS
InterPlanetary File System – Decentralized storage layer for context blobs.
Arweave
Permanent decentralized storage system, optionally used for MCO persistence.
EAS
Ethereum Attestation Service – Smart contract framework for storing attestations on-chain.
Gateway
Server that prepares or verifies MCOs. Can be run by user, DAO, or protocol provider.
Registry
Smart contract or database tracking allowed scopes, signers, or delegations.
🧰 SDK Specific Terms
buildMCO()
Generate and sign a Machine Context Object.
verifyMCO()
Verify a received MCO’s signature, timestamp, and scope.
generatePrompt()
Construct an LLM-friendly prompt using the context.
uploadToIPFS()
Store MCO payloads or claims on decentralized storage.
createDelegatedSigner()
Create a signer key with limited permissions and expiry.
generateZKClaim()
Generate a zero-knowledge proof for an attribute or credential.
🧠 Human-AI Interaction
Contextual Reasoning
LLM’s ability to adapt output based on personalized, verifiable user context.
Grounding
AI model's behavior is "tied" to real-world or structured data (e.g. on-chain facts).
Context Overloading
Risk of inserting too much data into a prompt, leading to token limit overflows or hallucinations.
Context Minimization
Only injecting the most relevant and scoped context for task efficiency and privacy.
Last updated