Give AI safe, scoped access to real-world systems - fast.
Turn your existing APIs into MCP tools with hosted runtime and scoped access built in. No servers to run. No custom MCP infrastructure to maintain.
Tools discovered automatically
Permission enforcement
Credential management
Real-world system access
Giving AI access to tools is harder than it sounds.
It's not just exposing an endpoint. To make models useful safely, you need:
- Authentication across users and projects
- Fine-grained permission boundaries
- Safe tool execution with audit trails
- Isolation between environments
- Visibility into usage and failures
This is where most implementations break down.
The layer between agents and real systems
Modern agents can call tools.
But once an action leaves the model, reliability becomes an infrastructure problem — retries, identity, duplicate prevention.
Execution is where those problems live. TengineAI handles that layer.
TengineAI makes execution reliable:
- Retries don't trigger duplicate side effects
- Every action has identity and a request ID
- Runs are logged so failures can be traced
Agents reason. Frameworks coordinate.
TengineAI executes the action safely.
Add execution reliability in minutes
Hosted runtime. Scoped access. Control plane included.
- No MCP server to deploy or maintain
- Built-in scoped authentication (account -> project -> user)
- Tool and permission management in one place
- Usage visibility and execution logs
Built for startups and SaaS teams that ship fast.
How it works
- 1
Create users and projects
Define isolation boundaries for tools and permissions.
- 2
Run tools reliably
Define tools in the dashboard and point them at your REST endpoints.
- 3
Enforce scoped access
Permissions are applied automatically at account, project, and user levels.
- 4
Run tools via MCP
Models connect to TengineAI via MCP through the SDKs you already use.
- 5
Let the model reason
The model decides at runtime. TengineAI enforces safety and execution.
TengineAI is the execution layer for AI systems.
Run real actions safely
Agents retry. APIs fail. TengineAI makes those retries safe.
- Retries are handled safely to prevent duplicate actions
- Keys revoke instantly — access shuts off across active sessions
- Runs are logged — every call has a Run ID and run history
- Your API receives the right identity (project/member) automatically
Most tools stop at orchestration. TengineAI continues into execution.
Works with any MCP client and any agent framework. TengineAI executes the actions your agent decides to take.
Production-ready tool execution via MCP
TengineAI does not require a custom client library. AI models connect directly using MCP through the SDKs you already use.
Below is an example using the Anthropic Python SDK.
1from anthropic import AsyncAnthropic
2
3client = AsyncAnthropic(api_key=CLAUDE_API_KEY)
4
5mcp_servers = [
6 {
7 "type": "url",
8 "url": "https://app.tengine.ai/mcp",
9 "name": "tengineai-mcp",
10 "authorization_token": TENGINEAI_MCP_API_KEY,
11 }
12]
13
14response = await client.beta.messages.create(
15 model="claude-sonnet-4-5",
16 max_tokens=2048,
17 messages=[
18 {
19 "role": "user",
20 "content": """
21 You are managing our AI-driven blog.
22
23 Your task is to:
24 1. Find trending posts on technology-related subreddits
25 2. Analyze the posts and generate three blog topic ideas
26 3. Select the strongest topic and create a draft blog post
27 4. Generate a featured image and update the draft
28 5. Write SEO metadata and update the draft
29 6. Publish the blog post
30
31 Proceed step by step.
32 """
33 }
34 ],
35 mcp_servers=mcp_servers,
36 betas=["mcp-client-2025-04-04"],
37)- No custom infrastructure required
- Tools are discovered automatically via MCP
- Permissions are enforced by TengineAI
- The model decides what to call at runtime
This is how agentic systems should be built.
Goals in the prompt. Tools discovered at runtime. Permissions enforced by infrastructure.
We run production AI systems on TengineAI.
Our AI-driven blog runs entirely on TengineAI. No external orchestration. No manual workflows.
The model reasons through the task at runtime. Tengine handles execution.
THE AI:
- Finds trending content
- Reasons about what matters
- Uses tools to create and update drafts
- Generates images and SEO metadata
- Publishes posts automatically
LIVE TOOL CALLS
TengineAI controls authentication, permissions, and tool execution.
Built for startups and SaaS teams shipping real AI systems.
This is for you if:
- You are building AI products or agentic systems
- You need AI to interact with real APIs
- You care about authentication, permissions, and security
- You don't want to host or maintain an MCP server
This is probably not for you if:
- You are only experimenting with prompts
- You want no-code automation
- You are not working with real backend systems
- You need an enterprise self-hosted MCP platform
You could build this yourself.
Building a production-grade MCP infrastructure means:
- Running and maintaining your own MCP server
- Designing and enforcing scoped authentication
- Building permission boundaries that don't leak
- Logging, monitoring, and failure handling
- Hardening it for scale and reliability
Most teams end up stitching together a fragile version of this - custom auth layers, ad-hoc tool wrappers, and brittle permission logic that breaks as they scale.
Building this properly is complex and time-consuming.
Instead plug in TengineAI and ship this week.
Start building with TengineAI.
Give AI safe, scoped access to your real systems - without running your own MCP infrastructure.