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Terms are organized alphabetically. Use Cmd/Ctrl+F to search for specific terms.

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A

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Agent

Definition: An autonomous software program that uses AI models to make decisions and perform tasks. In Agentflare: Agents connect through the Agentflare proxy to access MCP servers and other tools while providing full observability of their decision-making process. See also: MCP, Tool Calls

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Analytics

Definition: The systematic analysis of data to discover meaningful patterns and insights. In Agentflare: Performance analytics track agent behavior, resource usage, and decision patterns across all tool calls and interactions. See also: Performance Analytics, Cost Tracking

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C

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Cost Attribution

Definition: The process of assigning costs to specific operations, users, or resources. In Agentflare: Cost attribution tracks token usage, API calls, and resource consumption down to individual agent actions, enabling precise cost analysis and optimization. Example: 
{
  "tool_call": "database_query",
  "tokens_used": 1250,
  "estimated_cost": "$0.025"
}
See also: Cost Tracking, Performance Analytics

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Cost Tracking

Definition: Monitoring and recording expenses associated with AI agent operations. Usage: Enables teams to understand and optimize the financial impact of their AI deployments by tracking costs per tool call, session, or user. See also: Cost Attribution, Token Usage

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D

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Decision Reasoning

Definition: The logical process and context that leads an AI agent to make a specific choice or action. In Agentflare: Captured through thought tracing, decision reasoning provides transparency into why agents make specific tool calls or responses. See also: Thought Tracing, Memory Replay

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E

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Early Access

Definition: A program allowing selected users to test and provide feedback on features before general availability. In Agentflare: The early access program provides priority access to new Agentflare features and direct support from the Agentflare team.

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M

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MCP (Model Context Protocol)

Definition: A standardized protocol for communication between AI agents and external tools or services. In Agentflare: MCP servers act as the integration layer between your AI agents and various tools, with the Agentflare proxy sitting between them to capture observability data. Example: 
{
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "name": "database_query",
    "arguments": {"query": "SELECT * FROM users"}
  }
}
See also: MCP Proxy, MCP Server, Tool Calls

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MCP Proxy

Definition: An intermediary service that sits between AI agents and MCP servers to intercept and analyze communication. In Agentflare: The MCP proxy captures all interactions between agents and servers, providing observability without modifying your existing MCP implementation. See also: MCP, Proxy

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MCP Server

Definition: A service that implements the Model Context Protocol to provide tools and capabilities to AI agents. Usage: MCP servers expose functions like database queries, API calls, or file operations that agents can use to complete tasks. Example: 
const server = new MCPServer({
  name: "database-tools",
  version: "1.0.0",
  tools: [/* tool definitions */]
});
See also: MCP, Tool Calls

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Memory Replay

Definition: The ability to reconstruct and analyze an AI agent’s state and context at any point in its execution history. In Agentflare: Memory replay helps debug agent behavior by showing exactly what information the agent had access to when making specific decisions. See also: Thought Tracing, Decision Reasoning

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Migration Guide

Definition: Documentation that provides step-by-step instructions for transitioning from one system or version to another. In Agentflare: The migration guide assists teams in adopting Agentflare Agentflare with minimal disruption to existing workflows.

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O

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Observability

Definition: The ability to understand the internal state of a system based on its external outputs. In Agentflare: Agentflare provides comprehensive observability for AI agents, including thought processes, tool usage, performance metrics, and cost data. See also: Agentflare, Thought Tracing

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OpenTelemetry (OTEL)

Definition: An open-source framework for collecting, processing, and exporting telemetry data. In Agentflare: OTEL exporters allow integration with existing observability stacks like Datadog, Grafana, or Jaeger. Example: 
exporters:
  - type: otlp
    endpoint: "https://your-collector.example.com:4317"
See also: Observability, Telemetry

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P

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Performance Analytics

Definition: The measurement and analysis of system efficiency, speed, and resource utilization. In Agentflare: Tracks latency, throughput, error rates, and resource consumption for each agent interaction and tool call. Key Metrics:
  • Response time (p50, p95, p99)
  • Token usage per operation
  • Tool call success rates
  • Concurrent session capacity
See also: Analytics, Cost Tracking

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Proxy

Definition: An intermediary server that forwards requests between clients and servers. In Agentflare: The Agentflare proxy intercepts agent-to-server communication to provide observability without modifying your application code. See also: MCP Proxy

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T

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Agentflare

Definition: Agentflare’s observability platform that provides insight into AI agent thought processes and decision-making. Core Features:
  • Thought tracing for decision transparency
  • Memory replay for debugging
  • Performance and cost analytics
  • Multi-protocol support
See also: Observability, Thought Tracing

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Telemetry

Definition: Automated collection and transmission of data from remote systems for monitoring and analysis. In Agentflare: Telemetry data includes traces, metrics, and logs from agent interactions, exported via OpenTelemetry standards. See also: OpenTelemetry, Observability

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Thought Tracing

Definition: The capture and visualization of an AI agent’s reasoning process during task execution. In Agentflare: Thought tracing reveals the chain of reasoning that leads to each tool call or decision, making agent behavior interpretable and debuggable. Example Output: 
1. User requested database information
2. Evaluating available tools: database_query, file_read
3. Selected database_query based on SQL context
4. Formulating query parameters...
See also: Decision Reasoning, Memory Replay

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Token Usage

Definition: The consumption of computational units (tokens) by language models during processing. In Agentflare: Token usage is tracked per operation to enable accurate cost attribution and optimization opportunities. See also: Cost Attribution, Cost Tracking

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Tool Calls

Definition: Invocations of external functions or services by an AI agent to complete tasks. In Agentflare: Every tool call is captured with full context, including parameters, results, timing, and associated costs. Example: 
{
  "tool": "web_search",
  "parameters": {"query": "latest AI news"},
  "duration_ms": 450,
  "tokens_used": 230
}
See also: MCP, Agent

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Troubleshooting

Definition: The systematic process of identifying and resolving problems in a system. In Agentflare: The troubleshooting guide provides solutions for common integration issues, performance problems, and configuration errors.

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W

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WebSocket

Definition: A communication protocol providing full-duplex communication channels over a single TCP connection. In Agentflare: WebSocket connections enable real-time streaming of agent thoughts and tool calls to the Agentflare dashboard. Protocol Example: 
const ws = new WebSocket('wss://api.agentflare.com/v1/stream');
ws.on('message', (data) => {
  const event = JSON.parse(data);
  // Handle real-time agent events
});
See also: WebSocket Events, WebSocket Protocol

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WebSocket Events

Definition: Real-time messages transmitted over WebSocket connections to notify clients of state changes or new data. Common Events:
  • thought.start - Agent begins reasoning
  • tool.call - Tool invocation initiated
  • tool.result - Tool execution completed
  • session.end - Agent session terminated
See also: WebSocket, WebSocket Protocol

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WebSocket Protocol

Definition: The specification defining message format and communication rules for WebSocket connections. In Agentflare: Defines the structure for real-time agent monitoring, including authentication, message types, and error handling. See also: WebSocket, WebSocket Events
This glossary is continuously updated as new features and concepts are introduced. For the latest information, refer to the specific documentation sections linked from each term.
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