Teams connect agents to internal tools without a security model
Ad-hoc MCP servers expose APIs, tickets, and knowledge bases with shared tokens and no authorization or audit trail.
Platform Integration
Build production-ready MCP integrations that connect AI coding agents to internal systems — with schema design, authentication, authorization, audit, approval workflows, and client integration across enterprise platforms.
Why This Matters Now
Teams connect agents to internal tools without a security model
Ad-hoc MCP servers expose APIs, tickets, and knowledge bases with shared tokens and no authorization or audit trail.
Schemas and tool contracts are inconsistent across clients
Copilot, Codex, Claude Code, and Cursor each integrate differently — multiplying maintenance cost and increasing failure modes.
No approval path for privileged agent tool actions
Agents can mutate systems or retrieve sensitive context without human checkpoints, creating operational and compliance incidents.
Strategic context: MCP turns coding agents into enterprise systems participants — without secure design, auth, and audit, every new tool connection becomes a privileged access path you did not intend to create.
Capability Coverage
Identify high-value MCP opportunities across engineering, platform, and operations workflows with clear risk and ROI framing.
Design tool schemas, resource models, and server architecture that fit enterprise APIs and coding-agent client constraints.
Implement identity-aware access, least-privilege scopes, and service-to-service patterns suitable for privileged agent tooling.
Add logging, approval gates, and exception handling for tool calls that read sensitive data or mutate enterprise systems.
Integrate MCP servers with Copilot, Codex, Claude Code, Cursor, and related agent clients under a shared control plane.
Deliver test harnesses, operational documentation, and a support model so MCP integrations remain reliable after go-live.
Delivery Approach
Assess
Map candidate systems, data sensitivity, existing agent clients, and security requirements for MCP enablement.
Design
Design tool schemas, authZ model, audit requirements, approval workflows, and the first production integration slice.
Enable
Implement the MCP server, integrate approved clients, run security and functional tests, and document runbooks.
Adopt
Hand over support ownership, monitor usage, harden controls, and expand the factory to the next prioritized use cases.
Capability Programs
Proof & Perspectives
Engineering teams needed more consistent cloud-native development and DevOps practices to improve delivery reliability across environments and releases.
Retrieval-Augmented Generation (RAG) has become the dominant pattern for grounding enterprise LLM applications in proprietary data. Yet most organisations underestimate the architecture decisions required to move from a working demo to a production system that is accurate, cost-controlled, and auditable.
Ready to Begin
Work with our team to design an enablement program matched to your team's readiness, platform priorities, and delivery timeline.
Engagement Confidence
A direct, founder-led review before scope, delivery model, and commercial terms are proposed.
Response window
< 1 business day
Client coverage
India + global teams
Engagement format
Virtual, on-site, hybrid