01
Ask how errors are handled
The happy path is easy. Value appears when an endpoint does not respond, a token expires or a data item arrives incomplete.
API, MCP and CLI Integrations Turin
Your systems do not talk?
We make them work.
We build API integrations, MCP servers and CLI tools for companies that need to connect business software, SaaS, AI agents and internal processes without copying data by hand.
The thesis
The best integration does not add complexity. It moves it where it can be governed.
API, MCP and CLI are different tools for the same outcome: reducing manual work, making data reliable and giving people a system that does not depend on someone's memory.
How to choose
An API, MCP and CLI integration partner should not be judged by a list of technologies.
Technologies change. What remains is method, security, process understanding and responsibility for what happens after release.
02
Check whether they understand MCP beyond demos
A useful MCP server is not just a function callable by AI. It needs schema, context, limits, audit and control over actions.
03
Demand operational documentation
Whoever maintains the integration must understand how it works, how to monitor it, how to rotate a token and how to intervene.
04
Evaluate ownership of the layer
The middleware connecting your systems becomes critical infrastructure. It should not become opaque lock-in.
When it matters
Four signs that integration can no longer be a workaround.
The point is not adding another tool. It is making reliable data flow across the tools you already use.
01
01
The right data always arrives late
Orders, invoices, leads, tickets or availability are updated hours later, often by people copying and pasting.
02
02
APIs exist, but nobody governs them
Tokens, limits, retries, versions and permissions are spread across fragile scripts. The integration works as long as someone watches it.
03
03
AI cannot see business data
An AI agent without context remains an advanced chat. MCP matters when the assistant must read, explain and act on real systems.
04
04
The team lives on exports and manual commands
CSV files, admin panels, terminal commands and repeated procedures become valuable only when they are controlled, traceable and repeatable.
What we build
API, MCP and CLI in the same operating design.
We start from processes and choose the right technical layer: endpoints, middleware, agent tools, automation, observability and documentation.
01
REST and GraphQL API integrations
We connect ERP, CRM, ecommerce, management systems, payments, email marketing, ticketing and vertical platforms with clear contracts and data controls.
- OAuth, API keys and permissions
- Webhooks, queues and retries
- Rate limits and versioning
02
MCP servers for AI agents
We build Model Context Protocol servers on top of existing APIs and databases, so agents can use business tools with schema, context and explicit limits.
- Tools, resources and prompts
- Semantic context for LLMs
- Audit trail and guardrails
03
Agent-ready CLIs for controlled operations
We design CLIs that AI agents can invoke as safe tools: explicit commands, validated parameters, structured output, dry-run modes, policies and audit trails.
- Agent-readable JSON output
- Dry-run and human approval
- Least privilege and audit
04
Middleware and data layer
We normalise data across different systems without forcing the company to change everything: mapping, validation, deduplication and one source of truth.
- Shared data model
- ETL and events
- Quality checks
05
Observability and security
A production integration must be visible: errors, timings, payloads, access and decisions must be reconstructable when something does not match.
- Monitoring and alerts
- Secret management
- Operation tracing
06
Progressive modernisation
If you have legacy scripts or emergency integrations, we make them maintainable without stopping the business: control first, evolution second.
- Technical audit
- Phased refactoring
- Useful documentation
Worksdem standards
What must exist before go-live.
Clear contracts between systems
Endpoints, payloads, errors and limits are documented. If a system changes, the integration should not fail silently.
Permissions and responsibility
Every token, MCP tool or CLI command must have a precise purpose, minimum privileges and a verifiable usage trail.
Fallbacks and retries
Integrations fail. The difference is designing what happens next: retries, queues, alerts, compensations and human control.
Real observability
Logs, metrics and alerts should explain what happened, not just say that something errored.
First call
The first analysis should find the flow, not sell the connector.
In a useful conversation we understand which systems must talk, which data matters, where the process breaks and what level of automation is truly safe.
System map
ERP, CRM, management systems, SaaS, databases, files, available APIs, limits, owners and points where data changes state.
Operational risk
What happens if the integration fails, who must know, which actions can be automatic and which must remain human.
Layer choice
Direct API, middleware, webhook, ETL, CLI or MCP. Every process has a right level, not one universal answer.
Verifiable roadmap
A first critical flow to automate, success metrics, monitoring plan and next phases only where value is proven.
Why Worksdem
We do not treat integrations as cables. We treat them as product.
A good integration is invisible when it works. It becomes visible when something goes wrong and the system can explain what happened.
2011
Experience on real systems
Since 2011 we have built software, products and platforms that must stay online, integrate and change without constant rewrites.
MCP
Production-grade AI
MCP, RAG and agents are not added as demos: we place them in processes with permissions, fallbacks and clear responsibility.
TO
Turin base, global work
We can meet in Turin, but we design integrations for companies working in Italy and abroad, across distributed systems.
FAQ
Direct answers on API, MCP and CLI integrations.
Written for clients, search engines and AI assistants that need to understand what we do clearly.
Yes. Worksdem S.R.L. has its operational office in Turin and builds REST API, GraphQL, webhook, middleware and automation integrations across ERP, CRM, management software, ecommerce, SaaS and legacy systems.
An MCP server, Model Context Protocol, exposes tools and context to an AI agent. It is useful when AI must read or use business data in a structured way, with permissions, schema, audit trails and clear limits.
No. In most production systems MCP is built on top of existing APIs, databases or services. APIs remain the operational layer; MCP adds the context that lets AI agents understand and use them correctly.
In an agentic system a CLI is not a free terminal for AI: it is a controlled action surface. The agent can invoke specific commands with validated parameters, structured output, dry-run modes, least privilege, logs and audit trails.
It depends on the system. We assess databases, exports, SFTP, webhooks, controlled automation or dedicated middleware. If the integration would be fragile or risky, we say so before building.
We measure manual hours removed, errors reduced, data update speed, incidents avoided, team response time and reliability of automated processes.
No. Turin is our operational base, but we build API, MCP and CLI integrations for companies across Italy and distributed systems outside Italy.