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

Without O'Process	With O'Process
Manually search APQC PCF Excel (2017 rows)	Natural language query, instant results
Guess which KPIs apply to a process	Structured KPI suggestions from 3,284 metrics
Write job descriptions from scratch	Auto-generated with process-backed provenance
Cross-reference APQC + ITIL + SCOR manually	Unified 2,436-node taxonomy, one query

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:

Tool	Description	Key Parameters
search_process	Semantic search for process nodes	query (1-500 chars), lang (zh/en), limit (1-50), level (1-5)
get_process_tree	Get process subtree with children	process_id (e.g. "1.0"), max_depth (1-5)
get_kpi_suggestions	Get KPIs for a process node	process_id
compare_processes	Compare 2+ process nodes side-by-side	process_ids (comma-separated, 2+)
get_responsibilities	Generate role responsibilities	process_id, lang, output_format (json/markdown)
map_role_to_processes	Map job role to processes (curated-first, semantic fallback)	role_description (1-500 chars), lang, limit, industry
export_responsibility_doc	Export full responsibility document	process_ids (1+), lang, role_name
list_roles	List all 54 curated IT roles	lang, layer (strategy/architecture/delivery/operations)
get_role_definition	Get role profile with mapped processes	role_id (e.g. "sre"), lang
plan_it_roles	Recommend IT roles by team size	team_size (small/medium/large), lang
health_check	Health check — server status and data counts	(none)

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:

Layer	Roles	Examples
Strategy & Governance	10	CIO/CTO, CISO, Enterprise Architect, IT Auditor
Requirements & Architecture	8	Business Analyst, Solution Architect, Data Architect, UX/UI Designer
Delivery & Engineering	15	Developer, QA Engineer, DevOps, Release Manager, Scrum Master
Operations & Service	21	SRE, Capacity Planner, Service Desk, Change Manager, SOC Manager

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:

Prompt	Description	Parameters
analyze_process	Step-by-step process analysis workflow	process_id, lang
generate_job_description	Role responsibility document generation	process_ids, role_name, lang
kpi_review	KPI review and gap analysis workflow	process_id, lang

Resources

6 MCP resources for direct data access:

URI	Title	Description
oprocess://process/{id}	Process Node	Complete process node data
oprocess://category/list	Category List	All L1 process categories
oprocess://role/{role_name}	Role-Process Mapping	Process mappings for a role
oprocess://audit/session/{id}	Audit Session Log	Audit log for a session
oprocess://schema/sqlite	SQLite Schema	Public table schema (processes, kpis)
oprocess://stats	Framework Statistics	Process/KPI counts and version

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

Variable	Required	Description
GOOGLE_API_KEY	No	Enables semantic vector search (gemini-embedding-001). Without it, search falls back to SQL LIKE matching — all features still work.
OPROCESS_API_KEY	No	Bearer token for reverse-proxy auth layer.
OPROCESS_ALLOWED_ORIGINS	No	Comma-separated allowed origins for CORS.
LOG_LEVEL	No	Logging level (default: INFO)

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:

Key	Default	Description
boundary_threshold	0.45	Cosine distance threshold for BoundaryResponse
audit_log_enabled	true	Enable/disable SessionAuditLog
default_language	"zh"	Default language (zh/en)
rate_limit_max_calls	60	Max tool calls per window
rate_limit_window_seconds	60	Rate limit window duration (seconds)

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

Source	Entries	License
APQC PCF 8.0	2,017 processes	Royalty-free with attribution
ITIL V5	145 nodes	Practice names only (industry terms)
SCOR DS 14.0	175 nodes	Open-access standard
AI-era extensions	99 nodes	Original (MIT)
Total	2,436 processes
KPI metrics	3,284	From APQC PCF 8.0 Metrics
IT Role definitions	54 roles, 253 mappings	Curated (MIT)

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.