200+ Secure Tool Integrations for AI Agents
Connect your favorite tools to OpenClaw. Encrypted credentials. Egress-filtered. Fully audited.
210 integrations across 14 categories
MCP (Model Context Protocol) is the open standard that lets AI agents securely connect to external tools. Clawctl builds on MCP to give your agent instant, secure access to 200+ services — from GitHub and Slack to Salesforce and Stripe.
Every integration ships with encrypted credential storage, egress-filtered networking (your agent can only reach the APIs you approve), and a complete audit trail of every action. No custom integration code. No scattered API keys. No security trade-offs.
Paste your credentials, click connect, and your agent is live in under 60 seconds. One connection powers every agent in your workspace.
Developer Tools(30)
Code, CI/CD, version control, and development workflows
Your engineering team already uses dozens of developer tools every day — GitHub for code, Sentry for errors, Datadog for monitoring, Vercel for deploys. But connecting those tools to an AI agent usually means weeks of custom integration work, scattered API keys, and zero visibility into what the agent is actually doing.
Productivity(20)
Notes, docs, wikis, and knowledge management
Knowledge lives in too many places — Notion pages, Confluence spaces, Obsidian vaults, Google Docs. Your team wastes hours searching, copying, and reformatting information that an AI agent could surface instantly.
CRM & Sales(15)
Customer relationships, pipelines, and sales tools
Your sales team is drowning in CRM busywork — logging calls, updating deal stages, writing follow-up emails. Every minute spent on data entry is a minute not spent closing deals. And the data quality suffers because reps skip updates when they are busy.
Data & Analytics(15)
Databases, dashboards, and data processing
Getting answers from your data should not require filing a ticket with the analytics team. But giving an AI agent direct database access without guardrails is a recipe for disaster — runaway queries, exposed credentials, and no audit trail.
Cloud & Infrastructure(15)
Cloud providers, hosting, and infrastructure management
Managing cloud infrastructure manually does not scale. But handing your AWS keys to an AI agent without guardrails is a fast path to an expensive mistake — or worse, a security incident.
Finance(12)
Payments, accounting, and financial tools
Financial data is the most sensitive data your company handles. But finance teams are still doing manual reconciliation, chasing invoices, and pulling reports by hand — because nobody trusts giving an AI agent access to payment systems without rock-solid security.
Project Management(15)
Tasks, sprints, and project tracking
Project managers spend more time updating project management tools than actually managing projects. Copying status updates between Jira, Slack, and spreadsheets. Manually triaging backlogs. Chasing people for updates they forgot to log.
Storage & Files(12)
File storage, drives, and document management
Your files are scattered across Google Drive, Dropbox, S3 buckets, and local storage. Finding the right document means searching three different places and hoping the file name makes sense. Your AI agent could find and organize files instantly — if it had secure access.
AI & ML(15)
AI models, ML pipelines, and inference tools
Modern AI workflows chain multiple models together — using GPT-4 for reasoning, Whisper for transcription, DALL-E for images, and custom models for domain-specific tasks. Managing API keys for each provider, handling rate limits, and tracking which model did what becomes its own engineering project.
Security(10)
Auth, secrets, and security scanning
Security tools are supposed to reduce risk — but connecting them to AI agents often creates new risks. API keys in environment variables. Secrets in config files. No audit trail for what the agent accessed. Your security team would have a heart attack.
Design(10)
Design tools, assets, and creative workflows
Designers spend too much time on repetitive tasks — exporting assets, resizing images, organizing files, and updating design systems. Meanwhile, the rest of the team is waiting for assets they need to ship.
Marketing(15)
Email, social, ads, and marketing automation
Marketing teams juggle a dozen tools — email platforms, social schedulers, analytics dashboards, ad managers. Every campaign requires copying data between systems, pulling reports manually, and hoping nothing falls through the cracks.
Communication(15)
Chat, email, and messaging platforms
Communication tools are where work actually happens — but they are also where work gets lost. Important messages buried in Slack threads. Customer emails sitting in shared inboxes. Meeting action items forgotten the moment the call ends.
Other(11)
Miscellaneous integrations
Some integrations do not fit neatly into a single category — but they are no less important. E-commerce platforms, automation hubs, content management systems, and specialized tools all benefit from AI agent access.
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