Connect
Optimize
Secure
Range MCP Server
for AI Agents
Production-ready Range MCP server with extensible actions — plus built-in authentication, security, and optimized execution.
Range MCP Server
Built by 
StackOne
StackOne 
Coverage
13 Agent Actions
Create, read, update, and delete across Range — and extend your agent's capabilities with custom actions.
Authentication
Agent Tool Authentication
Per-user OAuth in one call. Your Range MCP server gets session-scoped tokens with zero credentials stored on your infra.
Agent Auth →
Security
Agent Protection
Every Range 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 Range call.
Tools Discovery →What is the Range MCP Server?
A Range MCP server lets AI agents read and write Range data through the Model Context Protocol — Anthropic's open standard for connecting LLMs to external tools. StackOne's Range MCP server ships with pre-built actions, fully extensible via the Connector Builder — plus managed authentication, prompt injection defense, and optimized agent context. Connect it from MCP clients like Claude Desktop, Cursor, and VS Code, or from agent frameworks like OpenAI Agents SDK, LangChain, and Vercel AI SDK.
All Range MCP Tools and Actions
Every action from Range's API, ready for your agent. Create, read, update, and delete — scoped to exactly what you need.
Record Interactions
- Record Interaction
Record integration activity for a user
Teams
- List Teams
Retrieve a list of teams associated with an organization
- Get Team
Retrieve details about a specific team
User Teams
- List User Teams
Get all teams a user belongs to using their user_id
Team Relations
- Update Team Relation
Make a user join or follow a team, or update their role
- Delete Team Relation
Remove a user from a team or stop following it
Updates
- List Updates
Retrieve a list of check-ins (updates)
Users
- List Users
Retrieve a list of users in an organization
- Get User
Retrieve full profile of a user by their user_id
Authenticated Users
- Get Authenticated User
Retrieve the user associated with the current API key
Find Users
- Find User
Search for a user by email address or linked integration account
User Profiles
- Update User Profile
Update the profile information of a user
User States
- Update User State
Update the state of a user (admin only)
Set Up Your Range MCP Server in Minutes
One endpoint. Any framework. Your agent is talking to Range in under 10 lines of code.
MCP Clients
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>"
]
}
}
}More Project Management MCP Servers
Azure DevOps
172+ actions
Bitbucket
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Jira
134+ actions
Confluence
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Trello
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Asana
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GitLab
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Range MCP Server 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
Range MCP Server FAQ
Range MCP server vs direct API integration — what's the difference?
A Range MCP server and direct API integration serve different use cases. Direct API integration is for software-to-software — backend code calling Range. A Range MCP server is for AI agents — MCP clients like Claude and Cursor, plus framework agents built with OpenAI, LangChain, or Vercel AI — discovering and calling Range at runtime. StackOne provides both.
How does Range authentication work for AI agents?
Range authentication for AI agents works through a StackOne Connect Session. Create one via the dashboard or the SDK — you get an auth link and ready-to-paste config for Claude Desktop, Cursor, and other MCP clients. Your user authenticates their own Range account; StackOne handles token exchange, storage, and refresh. Credentials never reach the LLM, and each user is isolated via
origin_owner_id.Are Range MCP tools vulnerable to prompt injection?
Yes — Range MCP tools can be vulnerable to indirect prompt injection. Any tool that reads user-written content — documents, messages, tickets, records, or free-text fields — is a potential vector. StackOne Defender scans every tool response before it enters the agent's context — regex patterns in ~1ms, then a MiniLM classifier in ~4ms. 88.7% accuracy, CPU-only.
What is the context bloat of a Range agent and how do I avoid it?
Context bloat happens when Range tool schemas and API responses eat your Range agent's memory, preventing it from reasoning effectively. A single Range query can return a massive JSON response, and connecting multiple tools compounds the problem. Tools Discovery and Code Mode reduce context bloat — loading only relevant tools per query and keeping raw responses out of the agent's context.
Can I limit which actions my Range agent can access?
Yes — you can limit which actions your Range agent can access directly from the StackOne dashboard. Toggle actions on or off, or restrict them to specific accounts, with no code changes to your agent. Session tokens can be scoped to exact actions so if one leaks, exposure stays contained.
Can I create custom agent actions for my Range MCP server?
Yes — you can create custom agent actions for your Range MCP server using Connector Builder. It's an integration agent your coding assistant (Claude Code, Cursor, or Copilot) can invoke to research Range's API, generate production-ready connector YAML, test against the live API, and validate before you ship.
When should I NOT use a Range MCP server?
Skip a Range MCP server if your integration is purely software-to-software — direct Range API integration is simpler when no AI agent is involved. For deterministic, compliance-critical operations (financial transactions, regulatory reporting), direct API gives you predictable behavior without agent-driven decision-making. MCP shines when AI agents need to dynamically discover and call Range actions at runtime.
What AI frameworks and AI clients does the StackOne Range MCP server support?
The StackOne Range MCP server supports both. MCP clients (paste-and-go apps): Claude Desktop, Claude Code, Cursor, VS Code, Goose. Agent frameworks (code SDKs you build with): OpenAI Agents SDK, Anthropic, Vercel AI, Google ADK, CrewAI, Pydantic AI, LangChain, LangGraph, Azure AI Foundry.
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.