Internal systems for employees
CRM, ERP, ticketing and HR tools exposed to Claude or ChatGPT so staff can query and update records from the assistant they already use.
Fewer tabs and fewer copy-paste errors
[ MCP Development ]
Give Every AI Assistant Safe Access to Your Systems
We build Model Context Protocol servers that expose your internal tools, data and workflows to Claude, ChatGPT, Cursor and your own agents through one standard interface. Each server ships with OAuth, scoped permissions and full call logging.
Works with
- Claude
- ChatGPT
- Cursor
- Claude Code
- Your own agents
[ Architecture ]
How an MCP Integration Is Structured
The protocol sits between AI clients and your systems. We keep auth and policy in the middle so every client gets the same rules.
AI clients
- Claude
- ChatGPT
- Cursor and IDEs
- Custom agents
Transport and auth
Connects clients securely and identifies the user behind each call.- Streamable HTTP
- stdio for local
- OAuth 2.1
- SSO provider
MCP server
Defines what the assistant can see and do.- Tools
- Resources
- Prompts
- Schema validation
Policy and audit
Applies permissions and records every action.- Scope checks
- Redaction
- Rate limits
- Call log
Your systems
- Internal APIs
- Databases
- SaaS apps
- File stores
[ Capabilities ]
What We Build Into an MCP Server
A useful MCP server is small, well described and strict about who can do what. Here is what we deliver.
- 01
MCP server development
Servers in TypeScript or Python on the official SDKs, exposing tools, resources and prompts with clear names and typed schemas.
- 02
MCP client integration
MCP client support inside your own app or agent, with tool discovery, session handling and safe rendering of results.
- 03
Remote MCP hosting
Streamable HTTP servers deployed on your cloud, Cloudflare or Vercel, with autoscaling, health checks and versioned releases.
- 04
OAuth 2.1 authorization
Spec-compliant OAuth with PKCE, dynamic client registration and SSO through Okta, Entra ID or Auth0, so users act as themselves.
- 05
Scoped permissions
Per-tool scopes, read and write separation, field-level redaction and approval prompts for destructive actions.
- 06
Tool design and evals
Tool descriptions and schemas tested against real prompts across several clients, so models pick the right tool with the right arguments.
- 07
MCP Apps and rich results
Interactive UI components returned from tools where clients support them, such as tables, forms and charts inside the chat.
- 08
Registry and distribution
Packaging and listing in the official MCP registry or a private internal registry, with install docs for each client.
One to three weeks
Your First Production MCP Server, Scoped in One Call
Tell us which system your team wants inside Claude or ChatGPT. We map the tools, scopes and approvals, then quote a fixed price.
Scope an MCP Server[ Use cases ]
What Teams Connect Through MCP
MCP turns one integration into access from every assistant your team already uses. These are the servers we build most.
Your product inside AI assistants
A public remote MCP server so your customers can use your SaaS from Claude, ChatGPT and other clients, listed in public registries.
A new distribution channel for your product
Governed data access
Read-only SQL and warehouse tools with row limits, approved views and query logging, so assistants answer data questions without raw database access.
Self-serve analytics without new risk
Shared tools for in-house agents
One tool catalog your LangGraph, OpenAI Agents SDK or Genkit agents all call, instead of each team rewriting the same integrations.
Integrations built once and reused
Developer tooling in the IDE
Servers that give Cursor, Claude Code and other coding agents access to internal docs, feature flags, logs and deploy status.
Coding agents with real project context
Knowledge and document servers
Resources and search tools over wikis, contracts and policies, with the user's own permissions applied to every lookup.
Grounded answers inside any assistant
[ Industries ]
Where Teams Connect AI Assistants First
The first server is usually the system people already copy and paste from all day.
Put your product inside the assistants your customers already use, with each customer's own permissions applied.
- Public remote MCP server
- Registry listing and install docs
- Usage analytics per tool
- OAuth with your existing login
SaaS and software
[ Client voices ]
Teams We Have Built With
Rated 4.9/5 on average across the platforms clients review us on.
Clutch5.0
GoodFirms5.0- Google5.0
- Upwork4.9
I had the pleasure of working with Sajal Tech on a travel website, and it was an incredible experience from start to finish. They demonstrated professionalism, clear understanding of requirements, and excellent communication throughout.
[ Access control ]
MCP Without Opening the Floodgates
MCP makes your systems reachable from many AI clients at once. These controls keep that access narrow and visible.
Users act as themselves
Every call runs under the signed-in user's own identity and permissions, never a shared admin key, so access matches what they have today.
Write actions need consent
Tools that create, change or delete data are separated, scoped and can require explicit user confirmation in the client.
Tool poisoning defenses
Tool descriptions are reviewed and pinned, outputs are sanitized, and untrusted content is marked so it cannot inject instructions into the model.
Complete call audit
Each request logs user, client, tool, arguments and result size, exportable to your SIEM for security review.
- OAuth 2.1 with PKCE
- SSO via Okta, Entra ID, Auth0
- SIEM export
- ISO 27001 practices
[ How we deliver ]
How We Ship Your MCP Server
We start with the handful of tools people will actually use, then expand once usage data shows what is missing.
3 to 5 days
Tool mapping
Pick the systems and actions to expose, define scopes and decide between local, internal remote or public deployment.
- Tool catalog
- Permission model
1 to 2 weeks
Server build
Implement tools, resources and prompts with schemas, wire OAuth and test in MCP Inspector and target clients.
- Working MCP server
- Client test results
1 to 2 weeks
Hardening and rollout
Add rate limits, redaction, logging and monitoring, deploy remotely and roll out to a pilot group of users.
- Hosted server
- Install guides
- Audit dashboard
Ongoing
Expand the catalog
Add tools based on usage and failed requests, track spec updates and keep compatibility with new client releases.
- New tools
- Usage report
[ Technology stack ]
Clients, SDKs and Hosting
We test every server against the clients your users actually run, because each one handles tools a little differently.
- Claude
- ChatGPT
- Cursor
- Claude Code
- Kiro
- Antigravity IDE
[ Pricing ]
What MCP Development Costs
Indicative starting prices. You get a fixed quote after a free scoping call based on the number of tools and systems.
Single-system MCP server
One MCP server wrapping one internal system or API with a focused tool set.
From$4,000
1 to 3 weeks
- Up to 8 tools and resources
- OAuth and scoped permissions
- Tested in 2 target clients
- 30 days of support
Remote MCP platform
Most chosenHosted MCP servers for several systems with SSO, audit logs and monitoring.
From$12,000
4 to 6 weeks
- Up to 4 connected systems
- SSO through your identity provider
- Redaction, rate limits and audit
- Private registry and install docs
Public MCP for your product
A customer-facing remote MCP server so users can work with your SaaS from AI assistants.
From$20,000
6 to 10 weeks
- Multi-tenant OAuth with consent
- MCP Apps for rich results
- Registry listing and docs
- Load testing and versioning
[ FAQ ]
MCP Questions, Answered
MCP is an open standard, introduced by Anthropic and now supported across many AI clients, that defines how assistants discover and call external tools and read data. You build one MCP server for a system, and any compatible client such as Claude, ChatGPT or Cursor can use it.
A single MCP server works across every client that supports the protocol, so you avoid maintaining separate integrations for each vendor. It also gives you one place to enforce auth, permissions and logging.
Local servers over stdio run on a developer's machine and suit personal or IDE tooling. Remote servers over Streamable HTTP are hosted centrally, support OAuth and are the right choice for teams, customers and anything touching shared business data.
Remote servers use OAuth 2.1 as defined in the MCP authorization spec, typically connected to your existing identity provider such as Okta, Entra ID or Auth0. Users sign in once in their client, and each tool call runs with their own permissions.
Only if it is given broad access. We separate read and write tools, apply per-tool scopes, require confirmation for destructive actions and log every call. Tool descriptions and outputs are also hardened against prompt injection.
A focused server for one system starts from $4,000, a hosted multi-system platform from about $12,000, and a public multi-tenant MCP server for your product from about $20,000. The main cost drivers are the number of tools, the auth setup and how many clients must be tested.
Mostly the official TypeScript and Python SDKs, with FastMCP for Python servers when it fits. We match your existing stack so your team can maintain the server after handover.
Yes. We package and publish public servers to the official MCP registry and other directories, with install instructions for each major client. For internal servers we can set up a private registry your staff can browse.
You own the code, schemas, tool descriptions and deployment configuration, running in your own cloud or edge account. We document everything and can maintain it as the protocol and clients evolve.
[ Contact ]
Let's build your next product together
Book a free strategy call and leave with a clear plan and estimate. No commitment.
- 01Pick a time that suits you
- 0230 minutes on scope, stack, timeline and budget
- 03Fixed-price proposal, NDA on request