Bring Project Management
to Pydantic AI
Learn how to connect COR to Pydantic AI and start using 13 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
What is the COR MCP Server?
Connect your COR account to any AI agent and take full control of your professional services project management and profitability orchestration through natural conversation.
What you can do
- Project Portfolio Orchestration — List all active projects, retrieve detailed high-fidelity status metadata, and access profitability metrics programmatically
- Task Pipeline Intelligence — Query tasks for any project, retrieve detailed technical metadata, and stay on top of your team's operational delivery in real-time
- Profitability Monitoring — Access high-fidelity financial insights and project health metrics to ensure sustainable growth directly through your agent
- Time Tracking Discovery — Access recorded technical time entries to understand workload distribution and project efficiency across your organization
- Resource Architecture — List team members, teams, and user profiles to understand and orchestrate your organizational structure programmatically
- Client Database Access — Query the complete high-fidelity directory of client organizations to maintain perfect contextual alignment for every project
How it works
1. Subscribe to this server
2. Retrieve your Personal API Token from your COR account (Settings > API Tokens)
3. Start managing your professional services growth from Claude, Cursor, or any MCP client
No more manual status updates or missing profitability gaps. Your AI acts as your dedicated project coordinator and profitability architect.
Who is this for?
- Project Managers — instantly retrieve task lists and project statuses using natural language commands without leaving your creative workspace
- Agency Leads — monitor high-fidelity profitability metrics and team utilization to ensure healthy business operations
- Operations Managers — verify technical time logs and team assignments to optimize resource allocation through simple AI queries
Built-in capabilities (13)
Check API Status
Create a new project
Get current user details
Get details for a specific project
Get details for a specific task
List customer clients
List COR projects
List defined task types
Optionally filter by project ID to isolate specific technical pipelines. List tasks
List team users
List users in a team
List organization teams
List recorded time entries
Why Pydantic AI?
Pydantic AI validates every COR tool response against typed schemas, catching data inconsistencies at build time. Connect 13 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.
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Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
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Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your COR integration code
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Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
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Dependency injection system cleanly separates your COR connection logic from agent behavior for testable, maintainable code
COR in Pydantic AI
COR and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect COR to Pydantic AI through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 3,400+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for COR in Pydantic AI
The COR MCP Server runs on Vinkius-managed infrastructure inside AWS — a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts. All 13 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in Pydantic AI only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
How Vinkius secures
COR for Pydantic AI
Every tool call from Pydantic AI to the COR MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
How do I find my COR API Token?
Log in to your account, navigate to Personal Settings > API Tokens, and generate a new high-fidelity Personal API Token.
Can I check project profitability via AI?
Yes! The get_cor_project tool allows your agent to retrieve high-fidelity profitability metrics and financial health data for any specific project.
How do I list my organization's teams?
Use the list_cor_teams tool to retrieve the complete high-fidelity directory of teams along with their unique identifiers for precise orchestration.
How does Pydantic AI discover MCP tools?
Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.
Does Pydantic AI validate MCP tool responses?
Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.
Can I switch LLM providers without changing MCP code?
Absolutely. Pydantic AI abstracts the model layer. your COR MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.
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Update: pip install --upgrade pydantic-ai