Re:amaze MCP Server
for AI Agents
Connect your AI agent to StackOne's Re:amaze MCP server and give it 33 MCP tools out of the box. Auth, tool execution, and security all managed.
StackOne 
Coverage
33 Agent Actions
Create, read, update, and delete across Re:amaze — and extend your agent's capabilities with custom actions.
Authentication
Agent Tool Authentication
Per-user OAuth in one call. Your Re:amaze MCP server gets session-scoped tokens with zero credentials stored on your infra.
Agent Auth →
Security
Agent Protection
Every Re:amaze tool response scanned for prompt injection in milliseconds — 88.7% accuracy, all running on CPU.
Prompt Injection Defense →
Performance
Max Agent Context. Min Cost.
Free up to 96% of your agent's context window to enhance reasoning and reduce cost, on every Re:amaze call.
Tools Discovery →What is the Re:amaze MCP Server?
A Re:amaze MCP server lets AI agents read and write Re:amaze data through the Model Context Protocol — Anthropic's open standard for connecting LLMs to external tools. StackOne's Re:amaze MCP server ships with 33 pre-built actions, fully extensible via the Connector Builder — plus managed authentication, prompt injection defense, observability, and agent execution runtime. Connect it from MCP clients like Claude Desktop, Claude Code, Cursor, Goose, and VS Code, or from agent frameworks like OpenAI Agents SDK, LangChain, and Vercel AI SDK.
All Re:amaze MCP Tools
Every action from Re:amaze's API, ready for your agent. Create, read, update, and delete — scoped to exactly what you need.
Articles
- Create Article
Create a new help article
- List Articles
Retrieve help articles with search and filtering
- Get Article
Retrieve a specific article by slug
- Update Article
Update an existing help article
Channels
- List Channels
Retrieve all communication channels for the brand
- Get Channel
Retrieve a specific channel by slug
Contact Notes
- Create Contact Note
Add a note to a contact
- List Contact Notes
Retrieve notes for a specific contact
- Update Contact Note
Update an existing contact note
- Delete Contact Note
Delete a contact note
Contacts
- Create Contact
Create a new contact
- List Contacts
Retrieve contacts with search and filtering
- Update Contact
Update an existing contact
Conversations
- Create Conversation
Create a new conversation or ticket
- List Conversations
Retrieve conversations with filtering and pagination
- Get Conversation
Retrieve a specific conversation by slug
- Update Conversation
Update an existing conversation
Messages
- Create Message
Add a message or reply to a conversation
- List Messages
Retrieve messages across all conversations or filtered
Response Templates
- Create Response Template
Create a new canned response template
- List Response Templates
Retrieve canned response templates
- Get Response Template
Retrieve a specific response template
- Update Response Template
Update an existing response template
Other (10)
- Create Contact Identity
Attach an email, mobile number, social handle to a contact
- Create Staff Member
Create a new staff user
- Get Contact Identities
Retrieve all identities for a contact
- Get Volume Report
Retrieve daily conversation volume statistics
- Get Response Time Report
Retrieve response time metrics
- Get Staff Report
Retrieve staff performance metrics
- Get Tags Report
Retrieve tag usage statistics
- Get Channel Summary
Retrieve channel-wise conversation breakdown
- List Satisfaction Ratings
Retrieve customer satisfaction survey ratings
- List Staff
Retrieve staff members for the brand
Re:amaze AI Agent Use Cases
Connect your AI agent to Re:amaze and help your team scale the support operations they run by hand today.
Use StackOne to connect your AI agent to your helpdesk, CRM, and messaging tools to automate ticket triage and priority routing.
ViewUse StackOne to connect your AI agent to your telephony, CRM, and messaging tools to automate voice call summarization and CRM logging.
ViewUse StackOne to connect your AI agent to your helpdesk, CRM, and messaging tools to automate SLA breach prediction and escalation.
ViewSet Up Your Re:amaze MCP Server in Minutes
One endpoint. Any framework. Your agent is talking to Re:amaze in under 10 lines of code.
Agent Frameworks
JSON{
"mcpServers": {
"stackone": {
"command": "npx",
"args": [
"-y",
"mcp-remote@latest",
"https://api.stackone.com/mcp?x-account-id=<account_id>",
"--header",
"Authorization: Basic <YOUR_BASE64_TOKEN>"
]
}
}
}Check More Customer Support MCP Servers
113+ actions
104+ actions
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67+ actions
Platform Resources
MCP Code Mode: Keeping Tool Responses Out of Agent Context
Anthropic's code_execution processes data already in context. Custom MCP code mode keeps raw tool responses in a sandbox. 14K tokens vs 500.
11 min
Comparing BM25, TF-IDF, and Hybrid Search for MCP Tool Discovery
Benchmarking BM25, TF-IDF, and hybrid search for MCP tool discovery across 916 tools. The 80/20 TF-IDF/BM25 hybrid hits 21% Top-1 accuracy in under 1ms.
10 min
Indirect Prompt Injection Defense for MCP Tools: A Technical Guide
MCP tools that read emails, CRM records, and tickets are indirect prompt injection vectors. Here's how we built a two-tier defense that scans tool results in ~11ms.
12 min
MCP vs A2A: Architecture, Security, and When to Use Each
MCP vs A2A: what each protocol standardizes, how they differ, their shared security risks including indirect prompt injection, and when to use one, both, or a hybrid architecture.
12 min
MCP vs API: What 200+ Connector Builds Taught Us
MCP wraps APIs, it doesn't replace them. After building 200+ connectors that serve both, here's when each approach wins.
14 min read
Re:amaze MCP Server FAQ
Does StackOne have a Re:amaze MCP server?
Re:amaze MCP server vs direct API integration — what's the difference?
How does Re:amaze authentication work for AI agents?
origin_owner_id.Are Re:amaze MCP tools vulnerable to prompt injection?
What is the context bloat of a Re:amaze agent and how do I avoid it?
Can I limit which actions my Re:amaze agent can access?
Can I create custom agent actions for my Re:amaze MCP server?
When should I NOT use a Re:amaze MCP server?
What AI frameworks and AI clients does the StackOne Re:amaze MCP server support?
Put your AI agents to work
All the tools you need to build and scale AI agent integrations, with best-in-class connectivity, execution, and security.