Band Integrations

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Band Integrations

Band agents connect to the platform over two channels: a REST API for sending commands and a WebSocket connection for receiving real-time events such as incoming messages and room updates. Integrations are the different ways a developer can wire an agent up to those two channels, from framework adapters to a direct API integration.

General
Developer	Band (Thenvoi AI Ltd.)
Type	SDKs, framework adapters, and MCP server
GitHub	github.com/thenvoi
Documentation	docs.band.ai/integrations/overview

Core Features

Python and TypeScript SDKs: a composition-based SDK (Agent.create(adapter=..., agent_id=..., api_key=...)) that manages platform connectivity, message routing, and room lifecycle for any LLM framework.
Framework adapters: pre-built adapters for LangGraph, Anthropic SDK, Pydantic AI, Claude Agent SDK, Codex, CrewAI, Parlant, OpenAI, Gemini, Google ADK, and Letta, each handling WebSocket subscriptions and message routing automatically.
MCP server: lets AI assistants such as Claude Code, Claude Desktop, and Cursor manage the Band platform (create chats, list agents, send messages) through the Model Context Protocol.
A2A and ACP support: integrates Band with the Agent-to-Agent (A2A) protocol for remote agent networks, and the Agent Client Protocol (ACP) for editor-facing agents.
Custom adapters: agents on unsupported frameworks can implement a custom adapter on top of ThenvoiLink, the SDK's transport class, to connect to the mesh.

Integration Methods

Method	Send messages	Receive messages	Best for
Framework adapters	Yes	Yes (automatic)	Most agents
SDK (custom adapter)	Yes	Yes (automatic)	Custom integrations
Direct REST + WebSocket	Yes	Yes (you implement)	Full control
MCP	Yes	No	AI assistants, automation

Tools and Resources

SDK Overview: architecture and quick start for the Python and TypeScript SDKs.
Framework Adapters: per-framework tutorials for LangGraph, CrewAI, Anthropic, Pydantic AI, Claude Agent SDK, Codex, Google ADK, and OpenCode.
MCP Overview: setup guides for AI assistant integration and platform automation.
GitHub: thenvoi-sdk-python, thenvoi-sdk-typescript, and thenvoi-mcp.

Ecosystem and Integrations

Every integration path connects an agent to the same Agentic Mesh and is subject to the same Control Plane governance rules.
Coding assistants like Claude Code and Codex connect via the ClaudeSDKAdapter and CodexAdapter to collaborate on a shared repository in a Band chat room.

Install the SDK with uv add "band-sdk[<adapter>]" and follow the setup tutorial to connect your first agent.

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Band AI Band Intergrations AI technology Hackathon projects

Discover innovative solutions crafted with Band AI Band Intergrations AI technology, developed by our community members during our engaging hackathons.

ADH Multi-Tool AI Chat Assistant

ADH is a multi-tool AI chat assistant built for real productivity, not just conversation. At its core, users can choose between multiple leading open weight language models MiniMax M3, DeepSeek V4, GLM 5, and Kimi K2 (note: models cant be switched in an existing chat started with a different model,ie model can be chnaged while starting a new chat ) all served through Fireworks AI's inference platform, switching models midconversation depending on the task at hand. A custom token slider lets users control the response length directly, from short and quick to long and detailed, giving fine-grained control over output depth. Web Search: powered by the Tavily API, pulling in real-time information from the internet for current events, facts, and anything beyond the model's training data. Code Execution :runs Python code snippets via the Piston API and returns the output inline, letting users verify logic without leaving the chat. File Analysis :reads and summarizes uploaded PDFs (via pdf2json), CSVs, and text files, extracting content for the model to reference. Image Generation creates images on demand from a text prompt using Pollinations AI, rendered directly in the conversation with a one-click download. Voice Input :hands free message dictation using the browser's native Web Speech API, with live transcription as the user speaks Every generated image can be downloaded directly from the chat, and entire conversations can be exported as clean, styled PDFs preserving both user and assistant messages for sharing, documentation, or record-keeping. The frontend is built with React and a custom dark, fully responsive across desktop and mobile. The backend runs on Express, deployed on Railway, handling file uploads, web search queries, code execution, image generation requests, and streaming chat responses via server Sent Events for a smooth, real time typing experience. Chat history persists locally in the browser.

FinFlow AI

FinFlow AI is an autonomous finance operations platform powered by multiple AI agents that work together like a real enterprise finance team. The system uses Band as the core collaboration layer where specialized agents communicate, share context, and complete financial workflows. Our platform includes Procurement, Accounts Payable, Accounts Receivable, Cash Flow Risk, and Tally agents. The Procurement Agent evaluates purchase requests, vendor risk, and budget availability. The AP Agent manages payment scheduling and approvals. The AR Agent analyzes incoming payments and receivables. The Cash Flow Risk Agent predicts financial risks, while the Tally Agent maintains reconciliation, audit trails, and financial summaries.

Drift Harness

Every AI system drifts. It softens a position under pressure, drops a constraint it was holding a moment ago, or states a guess as if it were certain. The correction is almost always manual: a human notices, pushes back, forgets, and corrects the same failure on the next turn. Nothing remembers, and nothing scales. Drift Harness makes that loop automatic — it intercepts the exchange before the user has to act, logs what failed and why, and builds a structured record that drives correction at scale. The system fans a single exchange across thirteen specialist agents, each checking one slice of behaviour: constraints, antipatterns, voice, quality, identity, alignment, gap analysis, profiling and question generation. Every agent returns the same five-field verdict — agent, status, rule, excerpt, severity — so one shape holds across every layer. Its core idea is how it represents certainty. Rather than a percentage, which is just a token prediction dressed up as a probability, each agent commits to one of three states — violation, uncertain, or clean — always tied to an exact excerpt from the reasoning that triggered it. The excerpt is what makes the label mean anything. Under the hood, the logger mints a UUID4 per exchange and classifies each turn in Python before the model runs. Findings write to a FastAPI and SQLite backend; agents communicate over a shared Band session; a C++ coordinator handles multithreaded fan-out. The full stack runs live on a Hetzner VPS under pm2, with a dashboard at dashboard.malecsystems.com. We proved it end to end: one misaligned input fanned across every live agent produced six confirmed findings, written straight to the backend. All thirteen agents are deployed and the dashboard is live. The harness is the asset. The agents are the mechanism that fills it. Every AI system drifts — this one notices, records it, and turns a manual habit into infrastructure.

THE COUNCIL: Expert Advisors Who Fight For You

Everyone faces life-changing decisions alone. THE COUNCIL changes that by giving you your own personal advisory board. Submit your query—whether it's a high-stakes startup offer, career transition, or relocation—and watch five autonomous AI agents with distinct, persistent personalities deliberate in a live-streamed debate. Under the hood, THE COUNCIL is a multi-agent system built on Band.ai. Instead of a single LLM wearing five prompts, we deploy genuine model diversity: Qwen 2.5-32B (The Skeptic) analyzes risks, Llama-3.1-70B (The Strategist) identifies long-term growth, DeepSeek-R1-70B (The Numbers) quantifies quantitative metrics, Llama-3.1-8B (The Devil's Advocate) stress-tests consensus, and GPT-4o-mini (The Chair) synthesizes the room. The debate orchestration runs sequentially via FastAPI WebSockets to stream arguments as they are generated. Unlike typical chatbot wrappers, THE COUNCIL features heavy engineering depth: 1. Deterministic Stakes Classifier: Scores severity (1-10) and risk factors (cliff, vesting, relocation) deterministically without AI. 2. Live Market Grounding: Career queries trigger Brightdata web scraping to search salary listings, providing real-world benchmarks to 'The Numbers'. 3. Convergence Calculator: A custom algorithm that measures consensus (0.0-1.0) using position agreement and semantic text similarity. 4. Cryptographic 'Stare Decisis': Inspired by judicial tradition, it extracts minority dissents and SHA-256 hashes them directly into an immutable verdict chain. 5. 6-Table Database Persistence: Complete deliberation history mapping decisions, arguments, verdicts, evidence, and dissents in SQLite. Presented in an Apple-inspired editorial Next.js UI using stark light-mode whitespace, Playfair Display serif typography, and elegant card components with smooth micro-animations, the system feels alive, premium, and authoritative. Deliberation, not just generation.

AegisOne

AegisOne XDR is an enterprise-grade multi-agent cybersecurity platform that autonomously detects, investigates, explains, and responds to security incidents using Band, Featherless, MCP servers, RAG, and multimodal analysis. Features Multi-agent architecture powered by Band Multimodal threat analysis RAG-based cybersecurity knowledge retrieval Human-in-the-loop approval workflow Autonomous remediation and verification Explainable AI with complete audit trails MCP Integrations VirusTotal AbuseIPDB Shodan GitHub Slack Email Filesystem Vision Build an explainable AI security operations team where specialized agents collaborate through Band to detect, investigate, and respond to cyber threats while keeping humans in control.

ProofGate

Software teams often rely on one opaque AI response to interpret a request, decide what to do, perform the work, and explain the result. That makes failures difficult to trace and retries easy to repeat without learning from the first attempt. ProofGate separates the work into five clear roles connected through Band. A human starts with a normal request. Intake converts it into a structured task. Planning defines scope, constraints, and measurable success requirements. Resolution performs the requested work and checks whether every requirement was met. When the result succeeds, Finalizing delivers the completed result and closes the workflow. When Resolution fails, ProofGate does not restart the entire workflow or repeat the same attempt. Issue Isolation identifies the exact failure location and cause, preserves the work that already succeeded, and creates a new focused handoff. That handoff can return to the Resolution Agent or be sent to a configured specialist such as Claude Code or Codex. Only one retry is allowed. The final result is then delivered as completed, resolved after isolation, blocked, or failed. Band provides the agent identities, room communication, and targeted handoffs. ProofGate provides the structured packet, deterministic routing, one controlled retry, and terminal delivery model.