Database MCP Servers
Secure MCP servers that expose Postgres, MySQL, MongoDB, or your data warehouse to AI agents — with read-only roles, query allow-lists, row-level security, and full audit logs.
MCP Server Development
Custom Model Context Protocol Servers for AI Agents
We engineer custom Model Context Protocol (MCP) servers that connect Claude, ChatGPT, Cursor, and bespoke AI agents to your real systems — databases, internal APIs, knowledge bases, ticketing, CRMs — with the security, audit trails, and observability enterprise IT teams actually approve.
Spec-compliant · OAuth + mTLS · Audit trails · VPC / on-prem
MCPSpec-compliant
TS/PyTypeScript & Python
SSEStreaming + HTTP
100%Audited tool calls
MCP Servers We Build
From data access servers to action-capable workflow servers — MCP integrations engineered with the security posture enterprise IT teams actually approve.
API & SaaS Connectors
MCP wrappers around Salesforce, HubSpot, Zoho, Jira, Linear, Notion, Slack, and bespoke internal APIs — so agents can read and act on your business systems through a single safe boundary.
Knowledge Base MCPs
MCP servers exposing Confluence, SharePoint, Drive, S3, or custom doc stores — with role-aware retrieval so users only see what their permissions allow.
Workflow Tool Servers
MCP servers that let agents fire approvals, draft documents, send emails, schedule jobs, and orchestrate multi-step business workflows — with human-in-the-loop gates where it matters.
Hardened Enterprise MCPs
OAuth, mTLS, scoped tokens, rate limits, redaction layers, and per-tool audit logs — built for environments where your security team needs to actually approve the integration.
Developer & DevOps MCPs
MCP servers exposing GitHub, GitLab, AWS, Azure, Kubernetes, observability stacks, and CI/CD pipelines — so engineering agents (Cursor, Claude Code) can ship work safely.
Industries We Serve
MCP servers shaped to the security, audit, and data-residency requirements of regulated and high-trust industries.
FinTech
Healthcare
Retail
EdTech
Logistics
Manufacturing
Professional Services
Real Estate
MCP Stack & Technologies
Official Anthropic MCP SDKs in TypeScript and Python, with battle-tested auth, transport, and observability tooling.
MCP TypeScript SDKProtocol
MCP Python SDKProtocol
Node.jsRuntime
Python 3.12+Runtime
FastAPIFramework
Express / FastifyFramework
OAuth 2.1Auth
mTLSAuth
DockerDeployment
KubernetesDeployment
OpenTelemetryObservability
Server-Sent EventsTransport
Our MCP Development Process
A six-step rhythm so MCP servers ship with security, auditability, and observability your enterprise can actually defend.
Tool Surface Audit
We map which internal systems agents need to access, which actions they can take, who owns the audit trail, and what your security team needs to approve before any code is written.
Tool Schema Design
Each MCP tool gets a precise JSON schema — input validation, idempotency keys, allow-listed parameters, and clear descriptions that agents can plan against safely.
MCP Server Implementation
Spec-compliant MCP servers in TypeScript or Python — STDIO for local clients, HTTP+SSE for hosted clients, with retries, rate limits, and graceful degradation.
Security & Governance
OAuth 2.1, mTLS, scoped tokens, per-tool permission checks, prompt-injection mitigations, redaction of secrets in responses, and structured audit logs.
Deployment & Wiring
Deployed to your VPC, on-prem, or our managed cloud — wired into Claude Desktop, ChatGPT (when supported), Cursor, or your custom agent runtime.
Observability & Care
OpenTelemetry traces of every tool call, structured audit logs, alerting on anomalies, and a retainer for new tool additions and spec upgrades.
Why Choose Hendoi for MCP Servers
Six commitments that decide whether your MCP integration becomes the strategic AI infrastructure layer — or a security incident waiting to happen.
Security by Design
OAuth 2.1, mTLS, scoped tokens, prompt-injection mitigations, and full audit trails — engineered so your security team can actually sign off on production deployment.
Full Observability
Every tool call is traced (OpenTelemetry), logged (with PII redaction), and surfaced on dashboards. You see what agents did, when, on whose behalf — always.
Spec-Compliant
We follow the official Anthropic MCP spec — STDIO, HTTP+SSE, resources, tools, prompts. Your servers work across Claude, ChatGPT, Cursor, and any future MCP-compatible client.
On-Prem & VPC Ready
Deploy MCP servers in your own infrastructure — no data leaves your perimeter. Particularly valuable for BFSI, healthcare, and government workloads.
Senior Engineers Only
MCP is new. We invested early, read the spec carefully, and built reference implementations. You get engineers who understand the protocol deeply — not just JSON-RPC.
Transparent Engagement
Weekly demos, direct access to engineers, signed SOWs with documented assumptions, and clear ownership of audit logs, secrets, and operational responsibility.
Engagement Models
Pick the commercial shape that matches where your MCP programme is — first pilot, multi-server platform, or evergreen maintenance.
MCP Pilot Sprint
A 3-5 week sprint to scope, build, and ship your first MCP server — a single internal system exposed safely to an AI agent, with audit logs and a security write-up.
- Single high-value tool surface
- Security review document
- Working server in your VPC
MCP Platform Build
A coordinated programme to build multiple MCP servers across your business systems — with shared auth, shared observability, and a governance model your security team approves.
- Multiple MCP servers
- Shared auth + observability
- Security governance docs
MCP Maintenance Retainer
Predictable monthly retainer covering new tool additions, spec upgrades, security patches, audit-log reviews, and on-call response for production incidents.
- Spec upgrade tracking
- New tool additions
- On-call incident response
Real-World Use Cases
Representative MCP integrations engineered across NBFC, D2C, knowledge, sales, and engineering workflows.
NBFC Customer Data MCP
MCP server giving customer-support agents read-only access to KYC, loan, and EMI records — with row-level scoping by agent identity and full audit trails for every lookup.
D2C Catalogue MCP
MCP exposing product catalogue, inventory, and order status to a customer-facing AI agent on WhatsApp — with rate limits and zero write access.
Internal Knowledge MCP
MCP server over Confluence and Drive — with role-aware retrieval so the AI assistant only surfaces docs the requesting employee has permission to read.
Salesforce MCP for Sales Agents
MCP wrapping Salesforce — agents read pipeline, update fields, draft emails, and propose next steps — every write action queued for human approval.
DevOps MCP for Engineering Agents
MCP exposing GitHub, Jira, and AWS read-only metrics to engineering agents like Cursor and Claude Code — with strict allow-listed actions and full audit logs.
Manufacturing MES MCP
MCP server bridging a Manufacturing Execution System and a plant-floor AI assistant — read-only access to production data, batch status, and downtime codes.
Frequently Asked Questions
Common questions enterprise architects and security teams ask about MCP server adoption.
What is the Model Context Protocol (MCP)?
MCP is an open protocol introduced by Anthropic in November 2024 for standardising how AI agents connect to external tools, data sources, and services. It lets one MCP server work across multiple AI clients (Claude, ChatGPT-compatible clients, Cursor, and custom agent runtimes).
Why build a custom MCP server instead of using ad-hoc API integrations?
MCP gives you a standardised, observable, and secure boundary between your AI agents and your internal systems. Auth, audit, rate limiting, and tool discovery work the same way across every agent, which is much easier for your security team to review and govern than dozens of one-off integrations.
Which AI clients work with MCP servers?
Claude Desktop and Claude API natively support MCP. Cursor supports MCP for developer tooling. ChatGPT and other vendors have published or signalled MCP compatibility. Custom agent runtimes (LangGraph, AutoGen) can also speak MCP — so your server is future-proof against client changes.
In which languages do you build MCP servers?
TypeScript (using the official MCP TypeScript SDK) and Python (using the official MCP Python SDK) are our defaults. We pick based on your team's existing language skills and the libraries needed for the systems being integrated.
How is security handled in MCP servers?
OAuth 2.1 for client auth, mTLS for service-to-service, scoped tokens, per-tool permission checks, prompt-injection mitigations, secret redaction in responses, rate limiting per agent/user, and structured audit logs surfaced to SIEM. We document the threat model for your security team.
Can MCP servers run on-premise?
Yes — MCP servers are just stateless services that can run anywhere. We deploy to your VPC, on-prem Kubernetes, or our managed cloud, depending on data-residency requirements.
How do you prevent prompt-injection attacks against MCP tools?
Strict input validation, allow-listed parameters, separation between system and user context, scoped read-only roles by default, idempotency keys for writes, and human-in-the-loop approval for destructive operations. We also document each tool's threat surface in the security write-up.
How long does an MCP server take to build?
A single-system MCP server typically takes 3-5 weeks including security review. A full multi-server MCP platform with shared auth and observability runs 8-14 weeks.