O'Process

AI-native process classification MCP Server. Query 2,436 processes and 3,284 KPIs from APQC PCF 8.0 + ITIL V5 + SCOR DS 14.0 + AI-era extensions.

Version: 0.5.0 | MCP SDK: Anthropic official mcp 1.26.0 | Protocol: 2025-11-25 | Coverage: 88%+

What It Does

O'Process gives AI assistants (Claude, GPT, etc.) real-time access to enterprise process knowledge. Connect it as an MCP Server, then ask natural language questions — the AI will call the right tools automatically.

Core capabilities:

• Process Search — "采购流程有哪些?" → returns matching process nodes with hierarchy, description, and confidence score
• Process Tree Navigation — browse the 5-level taxonomy (L1 categories → L5 activities)
• KPI Recommendations — get metrics for any process node (name, unit, formula, direction)
• Role-Process Mapping — "HRBP manages which processes?" → curated mappings with confidence scores and relation types (primary/shared/supporting)
• Role Knowledge Base — 54 curated IT roles across 4 layers (strategy/architecture/delivery/operations) with explicit process mappings
• Team Planning — recommend IT roles by team size (small/medium/large)
• Process Comparison — side-by-side diff of 2+ process nodes across all attributes
• Responsibility Document — generate complete job descriptions with provenance appendix

Why It Matters

Use Cases

Management Consulting — Process diagnostics. A manufacturing company's delivery cycle is 30% slower than competitors. Use search_process to locate SCOR Plan/Deliver/Make nodes, then get_kpi_suggestions to build a measurement framework.

HR Digital Transformation — Role-process mapping. CHRO needs to know what processes HR actually owns. Use get_process_tree on node 7.0 (Human Capital) to get the full L1→L4 hierarchy, then map_role_to_processes to map "HRBP" to standard processes.

Legal Due Diligence — Compliance audit. Cross-border M&A requires checking 12+ regulatory domains. Use search_process to locate relevant PCF nodes (corporate governance, tax, labor, environmental), then compare_processes to identify coverage gaps.

Internal Audit — KPI system design. Use get_kpi_suggestions for each process node, review coverage across efficiency/quality/cost/timeliness dimensions, identify missing metrics.

Quick Start

# Install
uv sync

# Run MCP Server (stdio — default)
uv run python -m oprocess.server

# Run with SSE transport
uv run python -m oprocess.server --transport sse --port 8000

# Run with streamable-http transport
uv run python -m oprocess.server --transport streamable-http --port 8000

Claude Desktop Configuration

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "oprocess": {
      "command": "uv",
      "args": ["run", "python", "-m", "oprocess.server"],
      "cwd": "/path/to/O-Process"
    }
  }
}

Tools

11 MCP tools with full input validation, structured output, and ToolAnnotations:

All tools return structured content (structuredContent + text) with result, provenance_chain, session_id, and response_ms. Each tool has outputSchema auto-generated from Pydantic models.

Invalid inputs raise ToolError (Tool Execution Error for LLM self-correction). All tools are annotated with readOnlyHint, idempotentHint, destructiveHint, and openWorldHint.

Role Knowledge Base (v0.5.0)

54 curated IT roles organized in 4 layers:

Each role includes bilingual (zh/en) definitions, aliases for fuzzy matching, explicit process mappings with confidence scores, and min_team_size thresholds for team planning.

Prompts

3 guided prompt templates for common workflows:

Resources

6 MCP resources for direct data access:

Authentication

For HTTP transports (SSE, streamable-http), authentication is handled at the reverse-proxy layer (e.g. Caddy with forward_auth or bearer_token directive). See deploy/README.md for Caddy configuration.

stdio mode requires no authentication (local process communication).

Environment Variables

No API key is required to run the server. All 11 tools work out of the box. Setting GOOGLE_API_KEY upgrades search_process and map_role_to_processes from text matching to semantic vector search.

Logging

Structured JSON logging (no extra dependencies):

# Default level: INFO (all tool calls logged)
export LOG_LEVEL=DEBUG  # DEBUG, INFO, WARNING, ERROR

# Output format (JSON):
# {"ts":"2026-03-16 12:00:00","level":"INFO","logger":"oprocess","msg":"tool.execute","tool":"search_process","session_id":"...","ms":4}

Configuration

Server behavior can be tuned via [tool.oprocess] in pyproject.toml:

Rate limiting is enforced via thread-safe RateLimiter. Exceeding the limit returns MCP error code -32000.

Governance-Lite

Transparent governance layer (non-blocking):

• SessionAuditLog — Append-only invocation log per session (failure-tolerant with escalation)
• BoundaryResponse — Structured fallback when semantic confidence is low (threshold: 0.45)
• ProvenanceChain — Derivation trail attached to every tool response
• Prompt Injection Mitigation — Description fields sanitized with [DATA_BEGIN]/[DATA_END] markers

Data Sources

Bilingual: Chinese (zh) + English (en).

Third-Party Attribution

APQC Process Classification Framework® (PCF) is an open standard developed by APQC, a nonprofit that promotes benchmarking and best practices worldwide. Used under APQC's royalty-free license for derivative works. To download the original PCF, visit apqc.org/pcf.

ITIL® is a registered trademark of PeopleCert group. This project references ITIL V5 practice names as industry-standard terminology. All descriptions are independently written and are not reproduced from ITIL publications.

SCOR® (Supply Chain Operations Reference) is a product of ASCM. This project references SCOR DS 14.0 process names as open-access industry-standard terminology. All descriptions are independently written.

Development

# Install dependencies
uv sync

# Lint
ruff check .

# Test (284 tests, 88%+ coverage)
pytest

# Full check (lint + test + benchmark)
ruff check . && pytest && pytest --benchmark-only

Project Structure

src/oprocess/
├── server.py              # MCP entry point (stdio/SSE/HTTP)
├── gateway.py             # ToolGatewayInterface + PassthroughGateway
├── config.py              # pyproject.toml config loader
├── validators.py          # Input validation + sanitization
├── prompts.py             # 3 MCP prompt templates
├── tools/
│   ├── registry.py        # Tool registration orchestrator
│   ├── search.py          # search_process + map_role_to_processes
│   ├── roles.py           # list_roles + get_role_definition + plan_it_roles
│   ├── resources.py       # 6 MCP resources
│   ├── _models.py         # Pydantic response models
│   ├── export.py          # Responsibility document builder
│   ├── helpers.py         # Provenance + comparison utilities
│   ├── serialization.py   # ToolResponse → ToolEnvelope
│   └── rate_limit.py      # Thread-safe rate limiter
├── governance/
│   ├── audit.py           # SessionAuditLog
│   ├── boundary.py        # BoundaryResponse
│   └── provenance.py      # ProvenanceChain
└── db/
    ├── connection.py       # SQLite + sqlite-vec connection
    ├── queries.py          # Process + KPI SQL queries
    ├── role_queries.py     # Role knowledge base queries
    ├── embedder.py         # Gemini embedding (with timeout + retry)
    └── vector_search.py    # sqlite-vec vector search

Tech Stack

• Runtime: Python 3.10+
• MCP SDK: Anthropic official mcp 1.26.0 (mcp.server.fastmcp)
• Protocol: MCP 2025-11-25 (structured output, ToolAnnotations, title)
• Validation: Pydantic 2.x (Annotated[..., Field(...)])
• Database: SQLite + sqlite-vec (optional vector search)
• Embeddings: gemini-embedding-001 (768-dim, 5s timeout, 2-retry)
• Packaging: uv + hatchling

Deployment

See deploy/README.md for production deployment on Alibaba Cloud with Caddy reverse proxy.

Live endpoint: http://8.138.46.17/mcp (streamable-http)

License

MIT — applies to all source code and AI-era original content.

Third-party framework data (APQC PCF, ITIL, SCOR) is used under their respective licenses. See Third-Party Attribution for details.