Spellbook Legal AI MCP Server for Pydantic AI 13 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Spellbook Legal AI through the Vinkius and every tool is automatically validated against Pydantic schemas — catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
agent = Agent(
model="openai:gpt-4o",
mcp_servers=[server],
system_prompt=(
"You are an assistant with access to Spellbook Legal AI "
"(13 tools)."
),
)
result = await agent.run(
"What tools are available in Spellbook Legal AI?"
)
print(result.data)
asyncio.run(main())
* 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
About Spellbook Legal AI MCP Server
Connect to Spellbook Legal AI and bring AI-powered contract drafting, review, and analysis to any AI agent. Trusted by 4,000+ in-house teams and law firms worldwide, Spellbook helps transactional lawyers draft and review contracts faster and more accurately.
Pydantic AI validates every Spellbook Legal AI tool response against typed schemas, catching data inconsistencies at build time. Connect 13 tools through the 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.
What you can do
- Contract Analysis — AI-powered review of contracts identifying risks, missing clauses, non-standard terms, and issues
- Clause Suggestions — Get AI-generated clause suggestions based on market standards and best practices
- Contract Comparison — Compare two contract versions to identify additions, deletions, and modifications
- Market Comparison — Compare contract terms against 2,000+ market precedents showing pro-buyer, pro-seller, and market-standard positions
- AI Clause Drafting — Generate AI-drafted clauses based on specified requirements, jurisdiction, and party position
- Contract Summarization — Generate concise summaries highlighting key terms, obligations, and risks
- Risk Assessment — Get comprehensive risk assessments with high, medium, and low risk issues and remediations
- Playbook Compliance — Check contracts against company playbooks to identify deviations from standards
- Clause Library Search — Search Spellbook's extensive clause library for standard, market-tested clauses
- Document Management — Upload, list, and search contract documents with filtering by status and type
The Spellbook Legal AI MCP Server exposes 13 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Spellbook Legal AI to Pydantic AI via MCP
Follow these steps to integrate the Spellbook Legal AI MCP Server with Pydantic AI.
Install Pydantic AI
Run pip install pydantic-ai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 13 tools from Spellbook Legal AI with type-safe schemas
Why Use Pydantic AI with the Spellbook Legal AI MCP Server
Pydantic AI provides unique advantages when paired with Spellbook Legal AI through the Model Context Protocol.
Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
Model-agnostic architecture — switch between OpenAI, Anthropic, or Gemini without changing your Spellbook Legal AI integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Spellbook Legal AI connection logic from agent behavior for testable, maintainable code
Spellbook Legal AI + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Spellbook Legal AI MCP Server delivers measurable value.
Type-safe data pipelines: query Spellbook Legal AI with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Spellbook Legal AI tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Spellbook Legal AI and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Spellbook Legal AI responses and write comprehensive agent tests
Spellbook Legal AI MCP Tools for Pydantic AI (13)
These 13 tools become available when you connect Spellbook Legal AI to Pydantic AI via MCP:
analyze_spellbook_contract
USE WHEN: - User wants to review a contract for risks - User needs to identify issues in a contract - User asks to "analyze this contract" or "review for risks" PARAMETERS: - document_id (REQUIRED): ID of the document to analyze - analysis_type (OPTIONAL): Type of analysis — "full" (default), "risks_only", "clause_check", "market_comparison" EXAMPLES: - "Analyze document 123 for risks" → call with document_id="123" - "Review this contract for issues" → call with document_id="123", analysis_type="full" - "Check clauses in document 456" → call with document_id="456", analysis_type="clause_check" Analyze a contract document for risks, issues, and suggestions
check_spellbook_playbook
Check contract compliance against a playbook
compare_spellbook_contracts
USE WHEN: - User wants to compare two versions of a contract - User needs to identify changes between drafts - User asks to "compare these contracts" or "show differences" PARAMETERS: - document_id_1 (REQUIRED): ID of the first document - document_id_2 (REQUIRED): ID of the second document - comparison_type (OPTIONAL): Type of comparison — "full" (default), "clauses_only", "risk_comparison" EXAMPLES: - "Compare documents 123 and 456" → call with document_id_1="123", document_id_2="456" - "Show differences between contract versions" → call with document_id_1="123", document_id_2="456", comparison_type="full" Compare two contract versions to identify differences
draft_spellbook_clause
USE WHEN: - User needs to draft a new clause for a contract - User wants AI to generate standard clause language - User asks to "draft a limitation of liability clause" or "write an indemnification clause" PARAMETERS: - clause_type (REQUIRED): Type of clause to draft (e.g. "Limitation of Liability", "Indemnification", "Confidentiality") - party_position (OPTIONAL): Which party position to draft for — "neutral" (default), "pro-buyer", "pro-seller", "pro-vendor" - jurisdiction (OPTIONAL): Jurisdiction for the clause (e.g. "New York", "Delaware", "California", "UK") - custom_instructions (OPTIONAL): Additional instructions or requirements for the clause EXAMPLES: - "Draft a limitation of liability clause" → call with clause_type="Limitation of Liability" - "Draft a pro-buyer indemnification clause for New York" → call with clause_type="Indemnification", party_position="pro-buyer", jurisdiction="New York" - "Write a confidentiality clause with custom instructions" → call with clause_type="Confidentiality", custom_instructions="Include data breach notification requirements" Draft a contract clause using Spellbook AI
get_spellbook_clause_suggestions
Get AI clause suggestions for a contract document
get_spellbook_document
Get detailed information for a specific contract document
get_spellbook_market_comparison
Shows pro-buyer, pro-seller, and market-standard positions. Get market comparison data for a specific clause type
get_spellbook_risk_assessment
Get a detailed risk assessment for a contract document
list_spellbook_documents
Supports filtering by status, document type, and date range. USE WHEN: - User wants to see all their contract documents - User needs to find contracts by status or type - User is exploring their document library - User asks "what contracts do I have" or "list my documents" PARAMETERS: - status (OPTIONAL): Filter by document status (e.g. "Draft", "In Review", "Finalized") - document_type (OPTIONAL): Filter by document type (e.g. "NDA", "MSA", "SOW", "Employment Agreement") - date_from (OPTIONAL): Start date filter (YYYY-MM-DD) - date_to (OPTIONAL): End date filter (YYYY-MM-DD) - page (OPTIONAL): Page number for pagination - page_size (OPTIONAL): Results per page (default: 25, max: 100) EXAMPLES: - "List all my contract documents" → call with no params - "Show contracts in review" → call with status="In Review" - "List NDAs" → call with document_type="NDA" List all contract documents in Spellbook
search_spellbook_clause_library
Search the Spellbook clause library for standard clauses
search_spellbook_documents
Search contract documents by keyword
summarize_spellbook_contract
Generate an AI summary of a contract document
upload_spellbook_document
USE WHEN: - User wants to upload a new contract for review - User needs to analyze a contract received from another party - User asks to "upload this contract" or "analyze this document" PARAMETERS: - file_name (REQUIRED): Name of the document file - file_content (REQUIRED): Base64-encoded file content or document text - document_type (OPTIONAL): Type of document (e.g. "NDA", "MSA", "SOW") EXAMPLES: - "Upload this NDA for review" → call with file_name="NDA.pdf", file_content="[base64 content]", document_type="NDA" - "Analyze this MSA contract" → call with file_name="MSA.docx", file_content="[base64 content]", document_type="MSA" Upload a contract document to Spellbook for analysis
Example Prompts for Spellbook Legal AI in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Spellbook Legal AI immediately.
"Analyze this NDA for risks and issues."
"Draft a pro-buyer limitation of liability clause for Delaware."
"Compare the market standard for indemnification clauses."
Troubleshooting Spellbook Legal AI MCP Server with Pydantic AI
Common issues when connecting Spellbook Legal AI to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiSpellbook Legal AI + Pydantic AI FAQ
Common questions about integrating Spellbook Legal AI MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
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?
Can I switch LLM providers without changing MCP code?
Connect Spellbook Legal AI with your favorite client
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Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Spellbook Legal AI to Pydantic AI
Get your token, paste the configuration, and start using 13 tools in under 2 minutes. No API key management needed.