Connecting autonomous AI assistants to internal enterprise databases and legacy systems is streamlined by AnythingMCP, a visual Model Context Protocol gateway with automated knowledge graph generation and granular access controls. Engineers can import OpenAPI specifications, Postman collections, SOAP WSDL files, or raw database credentials to generate standardized Model Context Protocol tools in minutes without writing custom code. The built-in knowledge graph automatically maps entity relationships across disparate databases and software platforms, teaching agents how to correlate customer records in CRM tools with live order histories in enterprise resource planning software. System administrators can enforce fine-grained access policies by restricting tool execution permissions to specific roles and scoping database operations to read-only queries with strict row limits. An interactive web console provides real-time tool inspection, payload testing, request tracing, and comprehensive audit logs that capture every upstream invocation with full parameter visibility. Enterprise teams can integrate identity providers through OAuth2, SAML single sign-on, and SCIM automated user provisioning while protecting sensitive credentials using AES-256-GCM encryption at rest. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. GNU AGPLv3 licensed.

One endpoint for every MCP server you run: MCPHub gathers local and remote Model Context Protocol servers behind stable URLs, so AI clients connect once and see what you allow. Claude Code, Cursor, and Cherry Studio can use four routes: everything at /mcp, a named group at /mcp/{group}, one server at /mcp/{server}, or semantic tool search at /mcp/$smart. Smart routing runs vector search on PostgreSQL with pgvector and an OpenAI-compatible key, so the model gets a shorter tool list. Servers attach over stdio, SSE, or streamable HTTP, OpenAPI services can be wrapped as MCP tools, and changes apply without downtime. In the other direction, MCP tools can be exported as an OpenAPI 3.0.3 spec for OpenWebUI and other OpenAPI clients. Bearer keys, OAuth 2.0 (client and server modes), and GitHub or Google sign-in in database mode control access, with per-user visibility for servers and groups. Encrypted per-user credentials let one shared server use each person's own key. Logs show tool-call activity, request status, and latency, health checks track each connection, and the dashboard controls which tools, prompts, and resources each server exposes. Large text tool results can be compressed, interactive MCP Apps are proxied through MCPHub routes, and a built-in market lets you browse a server catalog. Typical uses include a team-wide gateway, per-project groups, and direct single-server routes for debugging. 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.

With 2,600+ GitHub stars, MetaMCP solves the MCP server sprawl problem by aggregating any number of upstream servers into a single authenticated endpoint that any MCP client connects to once. Group servers into namespaces — development tools in one, data sources in another — then publish each namespace as its own SSE, Streamable HTTP, or OpenAPI endpoint with API-key authentication in headers or query parameters, or full OAuth per the MCP Spec 2025-06-18 standard. The aggregation engine discovers tools, resources, and prompts from all active servers in parallel, prefixes tool names with server identifiers to prevent collisions, and applies configurable middleware including tool filtering to reduce context-window bloat and description overrides to improve LLM comprehension. The web management UI lets you configure MCP servers with stdio, SSE, or Streamable HTTP transports, toggle servers active or inactive per namespace, create and revoke API keys per endpoint, and inspect discovered tools with their schemas. Nested MetaMCP support enables hierarchical architectures where one MetaMCP instance consumes another, creating multi-level tool organization with automatic name resolution. Compatible with Claude Desktop, Claude Code, Cursor, Open WebUI, and any MCP-compatible client through a single connection URL. The Docker container packages the TypeScript backend with PostgreSQL for configuration persistence, exposing the management UI on port 12005 and MCP endpoints on configurable ports. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

MCPJungle puts every MCP server your AI tools use behind one endpoint, so Claude, Cursor, Codex, and your own agents all connect to a single gateway instead of a tangle of per-client configurations. Register remote HTTP servers and local STDIO servers once, and their tools, prompts, and resources become discoverable through the gateway in one place. Tool groups expose curated subsets at their own endpoints, so a coding agent sees only the tools its job needs instead of hundreds of irrelevant ones competing for context. The dashboard gives you a visual registry of servers, tools, and groups for everyday management, while the CLI and REST API cover scripting and automation. Development mode runs with zero authentication for a personal setup; enterprise mode adds per-client tokens that allow-list exactly which servers each client may reach. User accounts and manual server initialization give teams a governed shared deployment, with OpenTelemetry metrics showing what clients call and how the gateway performs. Upstream servers can authenticate with bearer tokens or OAuth, so credentials stay centralized in the gateway rather than copied into every client config. Registry data persists in a local file for solo use or in PostgreSQL when the gateway becomes shared team infrastructure. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MPL-2.0 licensed.

Backed by the Linux Foundation with contributions from AWS, Cisco, IBM, Microsoft, Red Hat, and Shell, Agentgateway is the first data plane built from the ground up for AI agent workloads — providing a unified Rust-based proxy that handles conventional HTTP and gRPC traffic alongside MCP tool servers, A2A agent communication, and LLM inference endpoints through a single deployment. The LLM gateway routes requests to OpenAI, Anthropic, Gemini, AWS Bedrock, and other providers through an OpenAI-compatible unified API with per-tenant budget controls, spend tracking, prompt enrichment, load balancing across multiple model endpoints, and automatic failover when providers experience outages. The MCP gateway federates multiple tool servers behind one endpoint, supporting stdio, HTTP/SSE, and Streamable HTTP transports with built-in OAuth authentication compliant with the MCP auth specification, integrating Auth0 and Keycloak out of the box. OpenAPI integration exposes existing REST APIs as MCP-native tools without code changes, enabling legacy services to participate in agent workflows. Policy-based RBAC controls which agents access which tools, while OpenTelemetry integration provides distributed tracing across agent communication chains. Deploy as a standalone binary with flat YAML configuration or on Kubernetes using the built-in controller with Gateway API support for declarative infrastructure-as-code management. 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 gateway, every AI model: APIPark gives your applications a single, consistent API for OpenAI, Anthropic, Google Gemini, DeepSeek, and 100+ other models, and gives your team a portal to publish and share whatever gets built on top. Standardized request and response formats mean swapping a provider or rewriting a prompt never touches client code. Pair a model with a prompt template and it becomes a ready-made API for sentiment analysis or translation, listed in the developer portal with its own readme and generated API docs. Model Fallback swaps in the highest-priority available model when one misbehaves. API key balancing spreads traffic across several keys for the same provider. Already have REST services? Import an OpenAPI document, file the service under a category and tags, and let consumers subscribe, with optional manual review before anyone gets access. Any service can be switched on as an MCP tool that AI assistants can discover and call, and local open-source models can be deployed and exposed the same way. Usage charts follow requests, traffic, and tokens per service and consumer. Request logs flow out to files, HTTP endpoints, Kafka, NSQ, or Syslog. 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.

With over 5,000 GitHub stars since its June 2026 launch, OOMOL OpenConnector bridges the gap between AI agents and the real world by handling the authentication nightmare that stops LLMs from calling external APIs safely. The runtime connects to more than 1,000 SaaS providers — GitHub, Gmail, Notion, Slack, Microsoft, HubSpot, Google Workspace, and hundreds more — through 10,000+ prebuilt typed Actions that agents can discover and execute without ever touching raw credentials. OAuth2 flows, API key rotation, custom credentials, and no-auth providers are all managed centrally with AES-encrypted storage, scoped runtime tokens, and configurable action allowlists and blocklists that enforce least-privilege access. Agents interact through five access surfaces: the Model Context Protocol endpoint at /mcp for Claude and other MCP-capable hosts, a full REST API at /v1 for programmatic control, an auto-generated OpenAPI specification for code generation, a TypeScript SDK for application integration, and the oo CLI for local agent relay. The built-in Web Console provides browser-based administration for configuring OAuth apps, managing connections, inspecting action schemas, and reviewing execution logs with redacted inputs. Deploy via Docker Compose with SQLite for single-server setups, run from source on Node.js 22+, or push to Cloudflare Workers with D1 and R2 for edge deployment. 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.

The integrations your SaaS product offers its own users - that is what Nango, an open-source product-integrations platform, exists to build. It solves the repetitive infrastructure work behind every third-party API connection: OAuth flows, API key handling, token refresh, encrypted credential storage, rate-limit backoff, retries, and multi-tenant connection management. It ships pre-built auth configurations for 800+ APIs. Your users connect their accounts through an embeddable, white-label Connect UI, and your backend then reads or writes data through Nango's proxy, SDKs, or REST API without ever touching raw credentials. Integration logic is written as TypeScript functions covering actions, scheduled data syncs, and webhook processing - all running on one runtime with retries, checkpointing, and per-connection logs built in. Syncs pull records incrementally on a schedule, one-way or two-way, which suits RAG pipelines, search indexing, and keeping local copies of external data current. Selected actions can also be exposed as tool schemas or through a built-in MCP server, so AI agents operate on user-connected accounts without ever handling provider credentials. Auth support spans OAuth 2.0, OAuth 1.0a, API keys, basic auth, and JWT, and observability - logs, metrics, failure detection, and a reconnect flow for expired credentials - is scoped per customer connection for easier support debugging. Works with any backend language. Self-hosting on RepoCloud keeps all customer credentials and synced data on infrastructure you control, which matters for data residency and compliance requirements.

Cerbos decouples authorization logic from application code entirely, evaluating human-readable YAML policies in under one millisecond through a stateless Policy Decision Point that requires no application state synchronization or cross-network fan-out. Its custom decision engine benchmarks up to 17x faster than OPA-based alternatives. Access control policies use conditions expressed in Google's Common Expression Language, supporting role-based, attribute-based, and policy-based access control patterns including derived roles, scoped policies, and permissions-aware data filtering that pushes authorization predicates directly into database queries. The PDP exposes both gRPC and HTTP APIs with SDKs for JavaScript, Python, Go, Java, .NET, Rust, PHP, and Ruby, making integration a single function call regardless of tech stack. GitOps-native workflows treat policies as code with Git versioning, CI validation through GitHub Actions, coverage reports, breaking-change detection, and audit logs of every authorization decision for ISO27001, SOC2, and HIPAA compliance. Deployment flexibility spans Kubernetes sidecars, standalone services, systemd daemons, AWS Lambda functions, and WebAssembly-embedded PDPs that run authorization logic directly in browsers, serverless architectures, and edge devices. The Admin API manages policy lifecycle operations programmatically, while the built-in Playground and REPL provide interactive testing environments for policy authoring and debugging. 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.

OpenFGA answers the question 'can this user perform this action on this resource?' in single-digit milliseconds, implementing Google's Zanzibar paper as a production-ready authorization engine adopted by Auth0, Grafana Labs, Canonical, Docker, Agicap, and Read.AI. The server exposes both gRPC and HTTP APIs for authorization queries including Check, ListObjects, ListUsers, Expand, and the high-throughput BatchCheck endpoint that deduplicates and processes multiple authorization decisions in a single request. Authorization models combine relationship-based access control with role-based and attribute-based patterns through a purpose-built DSL that supports contextual tuples, conditional relationship tuples with CEL expressions, and time-based filtering via the ReadChanges API. Storage backends include PostgreSQL 14+, MySQL 8, and SQLite in beta, with an in-memory adapter for development and testing. Official SDKs for Java, .NET, Node.js, Go, and Python provide type-safe client integration, while a Terraform provider enables infrastructure-as-code management of authorization stores and models. The built-in browser playground at port 3000 lets developers visually model authorization schemas, write relationship tuples, and test access control queries interactively before deployment. OpenTelemetry instrumentation integrates with existing monitoring infrastructure, and Helm charts simplify Kubernetes deployment. A VS Code extension provides syntax highlighting and validation for FGA model files, and GitHub Actions automate model testing in CI/CD pipelines. A CNCF incubating project with transparent governance. 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.

API keys hardcoded in repos, database passwords pasted into CI variables, .env files emailed between developers - Infisical, the open-source platform for secrets, certificates, and privileged access management, is the answer to all three. Secrets live in versioned stores scoped by project, environment, and path, with fine-grained identity-aware access control and full audit logging on every read and change. Delivery covers every consumption pattern: CLI injection into local dev, SDKs for Go, Node.js, and Python, an HTTP API, agents, a Kubernetes Operator, and secret syncs that push to GitHub, GitLab, AWS Secrets Manager, and Vercel. Automatic rotation replaces credentials for PostgreSQL, MySQL, MSSQL, LDAP, AWS IAM, and Azure on a rolling schedule - new credentials issue while old ones stay temporarily valid, so nothing breaks mid-rotation. Dynamic secrets go further, generating ephemeral, time-bound database credentials on demand, and SSH access replaces static keys with short-lived CA-signed certificates that expire automatically. Secrets scanning catches hardcoded credentials in code and pipelines, certificate management automates X.509 issuance and renewal, and a built-in KMS handles encrypt/decrypt with central key control. Self-hosting keeps the keys to everything else on your own infrastructure.

With over 36,000 GitHub stars and adoption by organizations including Adobe, Shopify, and Roblox, HashiCorp Vault is the industry-standard platform for secrets management, encryption services, and privileged access control across hybrid and multi-cloud infrastructure. The key/value secrets engine stores arbitrary secrets with full versioning, soft-delete, and metadata tracking, while dynamic secrets engines generate on-demand, short-lived credentials for AWS, Azure, GCP, databases including PostgreSQL, MySQL, MongoDB, and MSSQL, and SSH access with automatic revocation after configurable lease periods. The PKI secrets engine dynamically issues X.509 certificates on demand with automatic rotation and ACME protocol support, eliminating manual certificate management workflows entirely. Encryption as a service through the transit secrets engine lets applications encrypt, decrypt, sign, verify, and generate HMACs without managing cryptographic keys directly, supporting AES-GCM-256, ChaCha20-Poly1305, RSA-2048/4096, ECDSA-P256/P384, and ED25519 algorithms. Authentication integrates with LDAP, OIDC/OAuth2, SAML, AppRole for machine-to-machine access, Kubernetes service accounts, AWS IAM, Azure Active Directory, and GitHub tokens. Fine-grained ACL policies use path-based rules with glob patterns and sentinel policies for programmatic enforcement. The integrated Raft storage backend provides high-availability clustering without external dependencies, while alternative backends include Consul, S3, DynamoDB, PostgreSQL, and MySQL. The built-in web UI provides a visual interface for browsing secrets, managing policies, configuring auth methods, and monitoring cluster health. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. BSL 1.1 licensed.

Describe the outcome once, in plain language, and a small crew of AI agents divides the work between them and reports back in the same chat. You type the request in the team chat; Boo Zero, the team lead, splits it into jobs on a shared board and hands each card to the teammate best placed to do it. Teammates run on Claude Code, Codex, Hermes, OpenClaw, or Clawboo's built-in runtime, and one team can mix them freely, so the researcher, the writer, and the coder can each work on their strongest tool. You follow every card live on the board and in the chat, watch the team graph to see who is doing what, and add a reviewer agent when a second pair of eyes matters. Finished work returns to Boo Zero, which pulls the pieces together and answers you in the chat. Ready-made teams from the marketplace cover marketing squads, dev teams, and research crews, and you can bring an API key from Anthropic, OpenAI, OpenRouter and more, a free local model through Ollama, or your ChatGPT subscription through the Codex CLI. Spend is tracked per team with budget warnings before costs surprise you. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Archestra delivers the enterprise AI infrastructure layer that organizations need when managing multiple LLM providers, MCP servers, and AI agents across teams becomes unmanageable. The LLM gateway routes requests across Anthropic, OpenAI, Azure, Bedrock, and DeepSeek with virtual API keys, per-team cost limits, and dynamic model routing — giving every developer one token for Claude Code, Cursor, or Codex while finance tracks spend per department. The MCP gateway authenticates tool calls with OAuth 2.1 and On-Behalf-Of tokens so each tool executes as the calling user, not a shared service account, eliminating credential sprawl. The private MCP registry lets teams publish custom tool servers with approval flows promoting servers from dev through staging to production, each environment maintaining its own credentials and network egress policies. The Kubernetes operator manages MCP server lifecycle — deploying containers, scaling, health-checking, and routing gateway traffic to local servers automatically. The agent runtime supports scheduled triggers, email and webhook invocations, sub-agent delegation, reusable skills, and sandboxed code execution with a K8s-native filesystem. Deterministic guardrails including Dual-LLM verification and Lethal Trifecta protections prevent dangerous tool calls before execution. Built-in OpenTelemetry traces and Prometheus metrics provide full observability without additional tooling. Docker deployment exposes the Admin UI on port 3000 and API on port 9000 with a single command. 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.

OneCLI gives every employee a sandboxed personal AI agent that works across company tools without ever seeing the real credentials it uses. Create an agent for each person, grant only the services that person may touch, and chat with it from its dashboard page or directly inside Slack channels and direct messages. The agent keeps its own filesystem, shell, memory, and skills between conversations, so follow up messages can redirect work in progress instead of starting over. Schedules wake agents at the right time to run recurring checks, reports, and follow ups without a person remembering to prompt them. When an agent calls Gmail, Salesforce, HubSpot, GitHub, Sentry, or another connected service, the gateway checks the request against team policy and injects the stored credential only for that call. Sensitive actions can pause for a deterministic human approval in chat, so sending an email, deleting a ticket, or changing a deal stage waits for your yes. Shared team connections let administrators connect a service once and grant it per agent, while memory remains readable and editable by the owner at any time. 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 agent breaks production at 3 a.m., "the model did it" is no incident report: Bernstein decides in advance what your AI agents may touch, then keeps receipts proving what they did. You write policy as code: which roles may do what, what needs human approval, and what must be recorded before a task counts as done. A deterministic scheduler with no model in the coordination loop turns each goal into parallel tasks, so replaying yesterday's plan reproduces yesterday's task graph exactly. Every coding task runs in its own git worktree behind merge gates; nothing lands on your main branch until tests, lint, and type checks pass. It drives the CLI agents you already use (Claude Code, Codex, Gemini CLI, Aider, Goose, dozens more), mixing cheap local models with heavy cloud ones in one run. Approvals can demand a hardware key touch, and role fences hold whatever an agent tries inside its task. The journal, lineage record, and optional tamper-evident audit chain capture every step, sealed into an Ed25519-signed receipt verifiable offline from the file alone. Non-code work gets the same treatment: an artifact contract names the deliverable (report, dataset, audit evidence pack), and the task completes on a signed receipt instead of a commit. You supervise from the browser dashboard or terminal UI, watching tasks, agents, approvals, and costs live. 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.