Sim Studio lets teams build, deploy, and monitor AI agent workflows by dragging blocks onto a visual canvas and wiring them into executable pipelines, backed by over 1,000 integrations. The React Flow editor represents each step as a node: LLM calls, tool invocations, conditional branches, and data transformations form directed acyclic graphs that run as complete agent pipelines. Every major LLM provider works natively, including OpenAI, Anthropic, Google Gemini, Groq, and Cerebras, plus local models through Ollama and vLLM. Integrations span Gmail, Slack, Microsoft Teams, Telegram, WhatsApp, Notion, Google Workspace, Airtable, GitHub, Jira, Linear, Perplexity, Firecrawl, PostgreSQL, Supabase, Pinecone, and Qdrant. Built-in tables provide a database layer, a file store offers shared team storage, and knowledge bases powered by PostgreSQL with pgvector enable retrieval-augmented generation. Finished workflows deploy as REST API endpoints, scheduled jobs, or Slack bots, with block-by-block execution traces for full observability. Real-time collaborative editing via Socket.io supports simultaneous multi-user construction. Alternatively, describe agent behavior in natural language and Sim assembles the workflow automatically. Built on Next.js App Router, Bun runtime, Drizzle ORM, and Tailwind CSS. 29,400+ GitHub stars and 100,000+ builders. Apache-2.0 licensed.

Buzz delivers the first production workspace where humans and AI agents operate as cryptographically equal team members on a self-hosted Nostr relay. The Rust-based backend stores every message, code patch, CI result, review comment, and workflow step as a signed Nostr event in a unified PostgreSQL-backed event log with Redis pub/sub for real-time presence and S3/MinIO for media storage. The integrated Git forge implements NIP-34, turning feature branches into dedicated channels where patches, reviews, and merge decisions live alongside the discussion that produced them — eliminating the split between chat tools and code hosts. Through the open Agent Client Protocol, Buzz natively supports Goose, Anthropic Claude Code, and OpenAI Codex as first-class channel members with scoped permissions, their own audit trails, and the ability to create patches, run workflows, and orchestrate multi-step automations via YAML-defined triggers including message events, reactions, schedules, and webhooks. The Tauri-based desktop client runs on macOS, Windows, and Linux, while buzz-cli provides agent-first JSON I/O for headless automation. Deploy via Docker Compose with the production bundle in deploy/compose/, Railway one-click, or build from source requiring Rust 1.88+, Node 24+, and pnpm. Multi-community mode scopes tenant data by domain with NIP-42 Schnorr authentication, rate limiting, and hash-chain audit logging. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed.

A looping agent burns money quietly until someone can see where it drifted, and PandaProbe is an observability and evaluation platform for AI agents that makes that drift visible step by step. Capture complete executions as sessions, traces, and spans spanning model calls, tool calls, multi-agent handoffs, and custom logic, then follow a looping or failing run back to the decision where it drifted. Score traces and sessions with agent-specific metrics, run asynchronous and sampled evaluations so judge models do not cost more than inference, and use lightweight trajectory signals to catch stalls, bad tool use, and regressions over time. Bring agents built with LangGraph, CrewAI, the Claude Agent SDK, the OpenAI Agents SDK, and other integrations, with MCP tool calls captured automatically where supported. Organize work by user, organization, and project, send data through an SDK or HTTP API with project keys, and query filtered, paginated traces when you need the raw record. Keep sensitive workflows local when that matters: prompts, traces, and evaluation results stay inside the deployment you run, instead of leaving for a hosted console. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

Close the laptop; the agents keep shipping. Cezar is an open-source control center that runs Claude Code, Codex, OpenCode, Copilot, and eight other coding agents in parallel on your own server, around the clock. Every task gets an isolated git worktree, so a dozen agents edit the same repository at once without colliding, and overflow waits in a queue. You watch each run live: the agent's text, its tool calls, token counts, and reported cost stream into one cockpit covering all your projects. The workspace dashboard separates what needs your answer, what is running, and what finished, and the usage view totals spend and tokens per project so a runaway task shows up in dollars, not surprises. Repeatable playbooks are plain Markdown skill files, chained into short YAML workflows that can mix a different agent per step, add checks and gates, and open pull requests; nothing merges on its own. Hand it a GitHub issue in one click, connect Jira or Linear to launch from your tracker, and schedule recurring maintenance with automations. Flip Autonomous and a run stops asking questions and just finishes; run the same task two or three times and keep the best diff. State lives in plain files, no database, and the responsive interface works from your phone. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Every major model provider behind one ChatGPT-style interface: LibreChat spans OpenAI, Anthropic, Google, Azure, AWS Bedrock, Vertex AI, Groq, Mistral, OpenRouter, DeepSeek, and any OpenAI-compatible endpoint including local Ollama. You can switch models mid-conversation and compare providers without changing tools. Its Agents framework builds no-code custom assistants with tool access via Model Context Protocol servers, file search over uploaded documents through an optional pgvector-backed RAG service, and a sandboxed Code Interpreter that executes Python, JavaScript, Go, C++, Java, PHP, and Rust. Artifacts render React components, HTML, and Mermaid diagrams directly in chat, and image generation works through DALL-E and other configured providers. Multi-user support is enterprise-grade, with OAuth, SAML, LDAP, and two-factor authentication, per-user conversation history in MongoDB, and Meilisearch-powered search across all messages and files, plus reusable presets, forkable threads, and persistent memory across conversations. The economics favor teams: instead of a ChatGPT Plus seat per person, everyone shares one instance billed per API token, with access to every provider rather than one - and providers see individual API calls, not your accumulated organizational knowledge. Deployment is Docker Compose; API keys and endpoints are configured through .env and librechat.yaml.

Got a research paper and no idea if anyone would pay for it? Academic Commercialization Agent answers with a cited triage report instead of a hunch. Type a topic or attach a paper PDF, pick a report language and scoring profile, and follow the run as it works through academic, patent, and market evidence. The result opens with a decision brief: an overall readiness score out of 100, the strongest evidence, the biggest risk, and a recommended first step. A scorecard breaks that number into technology readiness, manufacturing readiness, patent position, market accessibility, and evidence confidence, with a short reason behind each bar. The full report adds opportunities, risks, evidence limitations, reviewer notes, and a numbered reference list. Optional decision context captures who is deciding, what they own, and what choice is on the table, so the verdict reads as a license, invest, pilot, or spin-out call. Run history keeps every analysis searchable, interrupted runs resume from their last checkpoint, and two runs can be compared side by side. Reports export to Markdown or PDF and share by link, and a Sources search finds saved excerpts by ID or keyword. Six finished sample reports, one in Chinese, open without any key. A technology transfer office facing a pile of new disclosures can rank them in a first pass before spending expert time. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Enterprises keep buying AI tools and wondering why output does not compound, when the real gap is governance: nobody can say which agent owns what, what it may touch, or what it cost. Ybkkasi answers those three questions in one console for every MCP server, skill, agent, and AI application you run. Register each asset and move it through a lifecycle state machine from discovery to retirement, with 85 permission points deciding who can view, call, publish, or approve at every step. Work itself is organized as goals that break into projects and tasks, assigned to digital employees who each carry a home organization, a human supervisor, and a roster status. Approvals route through a dedicated center where lifecycle changes and sensitive actions wait for a human decision instead of happening silently. Every call is metered, so usage and cost reports attribute spend by department, by agent, and by skill, making showback a query rather than an argument. The audit log records who did what to which asset and when, giving compliance a trail they can actually read. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Agents that keep working after you close the tab: a13n gives a team one shared place to define them, run them, and watch what they did. In the Console, an administrator adds models from OpenAI, Anthropic, Gemini, Bedrock, Azure, OpenRouter, DeepSeek, Ollama, and others, then creates agents with instructions, skills, memories, connections, browsers, and sandbox environments. A Try agent button opens a conversation, and the Debug view lays out every run step by step, with model calls, tool calls, token counts, cache rates, and durations. Sessions and schedules keep a history of conversations and recurring jobs. The Usage page charts spend, runs, requests, and tokens by agent, model, or member across a time range. Findings analyzes traces, flags answer quality and tool failures, and lets reviewers confirm or dismiss each one with a suggested improvement. Each agent has a Connect to app screen with its ID, service URL, and API key, so applications can call it over an HTTP API or SDK. Workers lease runs from PostgreSQL and save checkpoints to object storage, so interrupted work resumes. Customer support teams, internal platform groups, and product builders use it to ship agent features without writing their own orchestration layer. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

Hermes Workspace serves as a dedicated command center for orchestrating autonomous AI agents, combining multi-model conversational flows with direct system execution in a unified web environment. Operators can execute multi-turn agent missions while observing live reasoning paths, tool dispatches, and file system mutations as they occur in real time. The built-in memory browser lets users inspect episodic recollections, search indexed agent knowledge bases, and edit persistent recall records directly from the interface. A comprehensive skill catalog provides instant activation and parameter tuning for over one hundred modular tool capabilities, ranging from web scraping to programmatic code generation. The embedded browser terminal delivers pseudoterminal sessions alongside running agents, enabling human operators to execute diagnostic commands and inspect project workspaces without switching windows. Conductor and Swarm management panels coordinate parallel sub-agent workers to break down complex research directives into asynchronous subtasks with automated status tracking. Integrated model switching allows teams to route individual execution steps dynamically between Anthropic Claude, OpenAI, OpenRouter, and self-hosted Ollama instances. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Customermates delivers a modern CRM purpose-built for teams who want practical customer management without enterprise-heavy complexity. The platform manages contacts, organizations, deals, services, and tasks through clean pipeline workflows while integrating AI agent capabilities, REST API access, webhook events, n8n automation connections, and Model Context Protocol tooling for AI-native operations. Team collaboration features include role-based permissions, comprehensive audit logging tracking every data change, and workspace organization for multi-team deployments. The deal pipeline provides customizable stages with drag-and-drop management, while task assignments and service tracking connect directly to contact and organization records for complete relationship context. API-first architecture exposes all CRM data through documented endpoints enabling custom integrations, reporting dashboards, and third-party tool connections. The n8n integration enables no-code workflow automation for lead routing, follow-up sequences, notification triggers, and cross-system data synchronization. Self-hosting requires only two files — a Docker Compose configuration and environment variables — with the published image at ghcr.io/customermates/customermates:latest running database migrations automatically on first boot. PostgreSQL provides the data layer with no additional infrastructure dependencies beyond a reverse proxy for TLS termination. The Community Edition includes unlimited users, unlimited records, full API access, n8n automation, and audit logging at zero cost. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

A control room for AI agents, where every run is recorded, capped, and ready to resume after a crash. Mission Control opens first with agent and run counts, tokens, success rate, and cost per day. A Templates page applies ready-made agents for code review, KYB due diligence, lead scoring, market monitoring, and release notes in a single screen. Every run gets a Report tab with the finished answer and a Timeline tab with each message, tool call, and charge. Tools are set to allow, ask, or deny. Spend caps pause a run instead of failing it. An agent can stop and ask a person a question. The Playground starts a run from a form and shows the same request as curl, so each agent doubles as an API. Triggers start capped runs on a schedule, from a signed webhook, or on a GitHub pull request. Learning mode keeps notes, skills, and workflows from each job so repeat work needs fewer tokens. Automated code review, customer research, and competitor digests are typical recurring jobs to hand it. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

One executive voice, backed by nine specialist agents, answers business questions from your own documents instead of generic management advice. Ask if a product line should be built or deferred and the reply cites your financial snapshot, roadmap, and legal notes, then lists the numbers behind the call and the next steps. The Agent Council covers strategy, finance, people, legal, operations, marketing, product, sales, and board communications, and each agent accepts its own instructions and model. A company profile stores mission, target customer, and competitors. Departments and Goals track owners, weekly check-ins, and at-risk or off-track status. Knowledge accepts PDF, Word, Excel, CSV, Markdown, and text files, and can sync from Google Drive, OneDrive, Confluence, or Notion. Memory records decisions and what the company has learned, and a built-in scheduler surfaces follow-ups and alerts on its own. The same executive answers in Slack, Discord, Telegram, Google Chat, Gmail, Outlook, or any MCP client, with spend approval thresholds that govern how it works with people. Founders get a chief of staff, small teams a fractional advisor, and board prep a head start before the next investor update. Demo companies are bundled for a quick tour. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

AgenTerm lets your AI agent work inside a remote computer's terminal with the owner's permission, through a relay server you host yourself. Your agent connects to the server over MCP and creates an invitation, single-use and expiring in fifteen minutes by default, or reusable across several devices; you privately share the generated connection command with the person who needs help. That person runs a small client on macOS, Linux, or Windows, reads what access means, and authorizes it; the client then dials out to your server, so the target computer needs no SSH service and no open inbound port. The agent can then run one-off commands with a chosen working directory, environment overrides, and timeouts, receiving stdout, stderr, and exit status, or hold an interactive session open, reading output as it arrives and typing answers to prompts. The person at the keyboard watches every command and its output in the client and can disconnect at any moment, and the client reconnects by itself after a network drop. Use it to troubleshoot a colleague's machine without swapping logs, help family through a terminal problem, or drive a development box with no agent or model account of its own. The relay itself is a single Go binary guarded by a management key, deployed with Docker Compose or systemd, with in-memory sessions and a health endpoint. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

CRW gives your apps and AI agents a private web data API that scrapes pages, crawls sites, maps links, and searches the web without sending every request to a hosted scraping service. Post a URL to the scrape endpoint and receive clean Markdown, HTML, screenshots, links, or structured JSON shaped by a schema you supply. Start a crawl when a whole section matters, then poll for progress while CRW walks pages asynchronously and returns the collected content in one job. Use map first to discover the URLs on a site before spending effort extracting pages you do not need. Connect agent tools through the MCP endpoint so assistants can search, scrape, and crawl from the same self-hosted service your applications call. Add browser rendering when JavaScript-heavy pages hide content from a plain HTTP fetch, and keep simpler pages on the fast lightweight path. Protect a public deployment with Bearer token authentication, your own reverse proxy, logging, and rate limits, or keep the service inside a private network for internal tools. Run one Docker container for the core API, or use the Compose stack when you want bundled search and rendering sidecars beside it. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

AgentConnect brings Claude Code, Codex, Grok Build, DeepSeek, and any other ACP-compatible coding agent into the chat channels and repositories where your team already works, each with a role of its own. Mention an agent in Slack, Microsoft Teams, Google Chat, Lark, Discord, or Telegram and it replies in the thread, calls on a colleague agent when needed, and keeps its session visible to teammates who can step in. Work can also start from a GitHub, GitLab, Gitea, or Azure DevOps pull request, a Linear issue, a webhook, or a schedule. The web console organizes the fleet into Agents, Sessions, Schedules, Tools and Skills, Knowledge, and Daemons views. Every agent gets its own memory, skills, MCP servers, workspace, and sandbox policy, and reviewed Knowledge pages can be published for all agents to search. Decisions route new conversations to specialist agents and pick the runtime and model for each session. Review bots can run several reviewers with separate instructions on one pull request. Set who may see each agent or session, which repositories it can touch, and which agents it may call. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

When an alert fires, OnGrid investigates it for you: an AI operations agent that correlates metrics, logs, traces, and topology, then names the root cause in plain language. A coordinator agent hands each question to specialist SRE, network, or database sub-agents, and the incident investigator walks the service graph for blast radius, queries Prometheus, Loki, and Tempo, and pins the cause to a line of source code before posting its report back to chat. Lightweight edge agents on every host dial out over a single tunnel, so no inbound ports are opened, and operators can reach any machine through an audited browser shell. The agent works through more than 26 read-only inspection tools in a sandbox, while anything that changes production waits behind an approval gate. Ask questions or receive reports in Slack, Telegram, Larksuite, DingTalk, or WeCom, and run it on Anthropic, OpenAI, GLM, DeepSeek, Gemini, Kimi, or any OpenAI-compatible endpoint. A workflow builder turns triggers, agents, tools, and notifications into repeatable automations, and a knowledge vault indexes runbooks, incident history, and repositories for search. Enroll Kubernetes clusters to inspect workloads and manage upgrades, or discover network neighbors, verify them over SNMP, and map them into the topology. Role-based access separates admins, users, and viewers. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

Give an outcome to Lucy, the built-in steward, and she assembles a fresh team of role-based agents inside a channel, with separate sessions and memory for each one. An official template library covers content, data, design, developer, legal, marketing, operations, product, and strategy workflows, from API documentation teams to pull request reviewers. Messages turn into Kanban tasks that agents claim, split into subtasks, submit for review, and close, and each task keeps its thread attached. A channel team graph shows who assigns work to whom, and Thinking mode branches a discussion into focused lines of reasoning that return conclusions to the parent. Agent Live tracks working, idle, and timed-out agents with a transcript viewer for every session, and an Insight dashboard charts messages, runs, tasks, and token usage over time. Finished work becomes artifacts you can review, regenerate, and publish. Pair a laptop or server as a Computer with a one-time command, and an inbox gathers mentions and replies. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

MCPProxy puts one safe endpoint in front of every MCP server your AI agents use, and it holds each new server in quarantine until a person approves it. Add stdio or HTTP servers on the Servers page, then review the captured tool definitions and scanner findings in the Review queue before any agent can call them. The Tools page lists every tool with a Read, Write, or Destructive tier, an approval state, and a usage count, plus switches to hide whatever you do not want exposed. Agents see a short set of discovery and call tools instead of the full catalog, and the Home dashboard estimates how much context that saves per request. The Activity Log records each call with its server, intent, status, and duration, and exports for audits. The Usage page charts calls per tool, response sizes, errors, latency, and activity over time, filtered by profile, client, or token. Profiles and agent tokens scope what each client may reach, a Secrets page keeps credentials out of config files, and a setup wizard connects Claude Code, Claude Desktop, Cursor, Windsurf, and VS Code. Platform teams and solo builders get one place to see and control everything their agents can touch. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.