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MODEL CONTEXT PROTOCOL (MCP)

MCP Server Development & AI Integration

MCP is the open standard that lets AI assistants and agents securely use your tools and data. We design, build and govern the MCP layer for your enterprise.

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Model Context Protocol (MCP)

One standard to connect AI with everything

Instead of building a one-off connector for every model and every system, MCP exposes your tools, resources and prompts through one open protocol that works with Claude, ChatGPT-compatible clients, IDE copilots and custom agents. We build the servers, add authentication, scopes and audit logging, and operate a central gateway.

What We Deliver

Capabilities included in Model Context Protocol (MCP)

Custom MCP servers

Expose ERPNext, Zoho, SAP, Dynamics, Tally, databases and internal APIs as MCP tools.

Auth, scopes & audit

OAuth, role-based permissions, per-tool scopes and tamper-evident logs.

MCP gateway

Central registry, rate limits, policy enforcement and monitoring for all servers.

Tool catalogs

Curated, documented and versioned tools so agents choose and use them reliably.

Data & resource servers

Read-only data, files and knowledge exposed safely as MCP resources.

Security hardening

Prompt-injection defences, input validation, sandboxing and least privilege.

Technology & Platforms

Tools and models we work with

MCP SDK (Python / TypeScript)FastAPINode.jsOAuth 2.1OpenAPIPostgresERPNext APIZoho APIPower BI APIDockerKubernetesClaude DesktopCursorVS CodeLangGraph

How We Deliver

A proven path from idea to production

Inventory tools & data

List systems, actions and data AI should reach.

Design the tool surface

Clear tool names, schemas and safe defaults.

Build & secure

Servers with auth, scopes, validation and logging.

Connect clients

Agents, desktop assistants, IDEs and chat channels.

Govern

Gateway policies, usage analytics and review workflows.

Use Cases

Where it creates business value

Ask your ERP anything

Natural-language queries and actions against ERPNext or other ERPs.

Conversational BI

Query Power BI and Zoho Analytics datasets from an AI assistant.

Support actions

Agents check orders, issue refunds and update tickets through approved tools.

DevOps assistants

Safe access to monitoring, logs and runbooks for IT operations.

Productivity connectors

Calendar, mail, documents and task tools behind one protocol.

Governed data access

AI reads curated datasets without direct database credentials.

Commercials & Engagement Models

Flexible ways to start and scale

Pick the model that fits your stage and risk appetite. Every quote is tailored to your scope - and every cost driver is explained upfront.

FIXED SCOPE

AI Discovery Workshop

1-2 weeks. Use-case discovery, data and architecture review, ROI model and a costed roadmap.

FIXED PRICE

Proof of Concept / Pilot

3-6 weeks. A working solution on your real data with success metrics and a clear go / no-go.

MILESTONE

Fixed-Scope Project

Scoped build with milestone payments, defined deliverables and acceptance criteria.

MONTHLY

Dedicated AI Pod

A cross-functional team - AI engineer, data engineer, solution architect, QA - on a monthly retainer.

SLA

Managed AI Operations

LLMOps monitoring, evaluation, tuning, cost control and incident response under a monthly SLA.

PASS-THROUGH

Usage-Based Costs

LLM tokens, vector databases and GPU compute billed at cost, or run in your own cloud account.

PERFORMANCE

Outcome-Linked Options

For well-measured processes, part of the fee tied to agreed KPIs such as hours saved or cases resolved.

LICENCE

Product & Platform Licences

Subscription for our reusable orchestrator, RAG and MCP accelerators to cut build time.

What drives the price

Scope & number of use cases

Data readiness & quality

Number of integrations (ERP, CRM, APIs)

Model choice & token volume

Cloud, private cloud or on-prem GPUs

Security, privacy & compliance needs

Languages & channels (WhatsApp, voice, web)

Accuracy targets & human review level

Support SLA & hours of coverage

Training & change management

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FAQ

Frequently asked questions

What is MCP (Model Context Protocol)?

MCP is an open protocol that standardises how AI applications connect to external tools, data sources and prompts through servers and clients.

Is MCP secure?

It can be, with the right design: scoped permissions, OAuth, input validation, human approval for sensitive actions, sandboxing and audit logs - all part of our delivery.

Which systems can you expose through MCP?

Practically anything with an API or database: ERPNext, Zoho, Power BI, SAP, Dynamics, Tally, Salesforce, ticketing and custom apps.

Do we need agents to use MCP?

No. MCP also powers AI desktop assistants and IDE copilots for individual users.