# Registry Review MCP Server Specification - Comprehensive Feedback
**Spec Version:** 1.0.0
**Review Date:** November 11, 2025
**Reviewers:** 4 specialized agents (2 domain experts, 2 MCP experts)
**Overall Assessment:** B+ (Good architectural foundation with critical implementation gaps)
---
## Executive Summary
The specification demonstrates **strong architectural understanding** and excellent alignment with MCP primitives (Prompts > Tools > Resources). The human-AI collaboration philosophy is well-articulated, and the workflow decomposition is sound. However, four major categories of issues prevent immediate implementation:
1. **Domain Gaps** (30% incomplete) - Missing critical workflow features like batch processing, SharePoint integration, and proponent correction loops
2. **Real-World Data Gaps** (40% incomplete) - Cannot handle GIS files, legal documents, or structured field extraction required by actual checklists
3. **MCP Protocol Gaps** (25% incomplete) - Missing discovery prompts, inadequate error handling, insufficient logging
4. **Implementation Gaps** (60% incomplete) - No concrete code examples, incorrect configuration syntax, severely underspecified testing
**Recommendation**: Address Critical and High Priority items (estimated 2-3 days of spec work) before implementation begins.
---
## Findings by Priority
### ⚠️ CRITICAL - Blocks Implementation
These issues will cause immediate failure or prevent development from starting:
#### 1. Missing Batch Processing Architecture (Domain)
**Impact:** Cannot address Becca's primary use case - Ecometric's 70-farm batch submissions
**Evidence:** Transcripts repeatedly emphasize batches of 45-70 projects as "urgent" automation target
**Current Spec:** Focuses exclusively on single-project workflows
**Required:**
```python
# Add to Tool 1: create_session
async def create_batch_session(
batch_name: str,
projects: list[dict], # List of {project_name, documents_path}
methodology: str = "soil-carbon-v1.2.2"
) -> dict:
"""Create session for batch of related projects"""
pass
# Add new workflow prompt
@mcp.prompt()
def batch_review() -> list[base.Message]:
"""Process multiple projects in parallel with aggregated reporting"""
pass
```
---
#### 2. Missing GIS File Handling (Real-World Data)
**Impact:** Fails 3 of 20 requirements (Project Area, Land Tenure, Monitoring Plan)
**Evidence:** Checklist requires "GIS shapefiles and maps"; example data contains `.shp` files
**Current Spec:** Only processes PDF files (line 370-437 in `discover_documents`)
**Required:**
```python
SUPPORTED_FILE_TYPES = {
".pdf": "document",
".shp": "gis_shapefile",
".shx": "gis_index",
".dbf": "gis_attributes",
".geojson": "gis_geojson",
".tif": "imagery",
".tiff": "imagery"
}
@mcp.tool()
async def extract_gis_metadata(filepath: str) -> dict:
"""Extract metadata from GIS files using fiona/geopandas"""
# Returns: area, feature count, CRS, bounding box
pass
```
**Dependencies to add:**
```toml
dependencies = [
# ... existing ...
"fiona>=1.9.0",
"geopandas>=0.14.0",
]
```
---
#### 3. Incorrect pyproject.toml Syntax (Implementation)
**Impact:** `uv sync` will fail with current configuration
**Current Spec (line 1815-1828):**
```toml
[tool.uv]
dev-dependencies = [ # ❌ WRONG SYNTAX
"pytest>=8.0.0",
]
```
**Corrected:**
```toml
[dependency-groups] # ✅ Correct for modern uv
dev = [
"pytest>=8.0.0",
"pytest-asyncio>=0.23.0",
]
[tool.uv]
exclude-newer = "2025-11-11T00:00:00Z"
```
---
#### 4. Missing Server Entry Point (Implementation)
**Impact:** No way to actually run the MCP server
**Current Spec:** Shows configuration but never implements `server.py`
**Required:**
```python
# src/registry_review_mcp/server.py
import sys
import logging
from mcp.server.fastmcp import FastMCP
from mcp.server.fastmcp import Context
from mcp.server.session import ServerSession
# CRITICAL: Log to stderr for STDIO transport
logging.basicConfig(
level=os.getenv("LOG_LEVEL", "INFO"),
format="%(message)s",
stream=sys.stderr
)
mcp = FastMCP("Regen Registry Review")
# Register all tools
from .tools import session_tools
@mcp.tool()
async def create_session(
project_name: str,
documents_path: str,
methodology: str = "soil-carbon-v1.2.2",
project_id: str | None = None,
proponent: str | None = None,
ctx: Context[ServerSession, None]
) -> dict:
"""Create new review session"""
return await session_tools.create_session(
project_name, documents_path, methodology, project_id, proponent, ctx
)
# Register prompts
from .prompts import initialize
@mcp.prompt()
def initialize_prompt(
project_name: str,
documents_path: str,
methodology: str = "soil-carbon-v1.2.2"
) -> list[base.Message]:
"""Initialize new review session"""
return initialize.create_messages(project_name, documents_path, methodology)
if __name__ == "__main__":
mcp.run()
```
---
#### 5. Missing `/list-capabilities` Prompt (MCP Protocol)
**Impact:** Violates MCP best practice; users can't discover available features
**Evidence:** MCP Primitives doc states "I highly recommend you set up inside all your MCP servers"
**Required:**
```python
@mcp.prompt()
def list_capabilities() -> list[base.Message]:
"""List all MCP server capabilities"""
return [
base.AssistantMessage("""
# Regen Registry Review MCP Server
## Workflow Prompts
- `/initialize` - Create review session
- `/document-discovery` - Index and classify documents
- `/evidence-extraction` - Map requirements to evidence
- `/cross-validation` - Check consistency
- `/report-generation` - Generate draft review
- `/human-review` - Present findings
- `/complete` - Finalize and export
## Tools (20+)
[Full list of tools with signatures]
## Resources
- `checklist://template/{methodology_id}` - Requirement templates
- `session://{session_id}` - Session state
- `documents://{session_id}` - Document index
""")
]
```
---
#### 6. Missing Example Checklist JSON (Implementation)
**Impact:** Cannot test any workflow without actual requirement data
**Current Spec:** Provides schema (Appendix B) but no data
**Required:** Create `/data/checklists/soil-carbon-v1.2.2.json` with actual requirements from `examples/checklist.md`
---
### 🔴 HIGH PRIORITY - Needed for MVP
#### 7. Structured Field Extraction (Real-World Data)
**Impact:** Cannot extract required evidence types (dates, names, areas, ownership)
**Current Spec:** Only extracts unstructured text snippets
**Required:**
```python
@mcp.tool()
async def extract_structured_fields(
document_id: str,
session_id: str,
field_schema: dict, # {"owner_name": "string", "area_hectares": "float"}
ctx: Context
) -> dict:
"""Extract specific structured fields using pattern matching and table parsing"""
# Use pdfplumber for tables + regex for fields
# Return confidence score per field
pass
```
---
#### 8. SharePoint Integration or Workaround (Domain)
**Impact:** Becca must manually download files from SharePoint (negates time savings)
**Current Spec:** Deferred to "Phase 2" with no details
**Options:**
- **Option A (MVP):** Document manual workaround clearly
- **Option B (MVP+):** Add read-only SharePoint connector using Microsoft Graph API
**If Option A, add to spec:**
```markdown
## MVP Limitations
### Manual Document Collection Required
The MVP works with **local files only**. For Ecometric projects:
1. Access SharePoint: [URL]
2. Navigate to project folder: `{year}/{project_id}/`
3. Download entire folder to local directory
4. Run `/initialize` with local path
**Time cost:** ~5-10 minutes per batch
**Automation target:** Phase 2 (SharePoint MCP connector)
```
---
#### 9. Proponent Correction Workflow (Domain)
**Impact:** Cannot handle iterative review loops (common scenario)
**Current Spec:** Assumes documents are either correct or flagged for human review
**Required:**
```python
# Add to Tool 10: generate_review_report
# Include correction request functionality
# Add new tool
@mcp.tool()
async def request_corrections(
session_id: str,
requirement_ids: list[str],
correction_notes: dict, # {req_id: "message to proponent"}
ctx: Context
) -> dict:
"""Generate correction request for proponent"""
# Mark session as "pending_proponent_revision"
# Generate correction report
# Update requirement statuses
pass
# Add new prompt
@mcp.prompt()
def revision_handling(session_id: str) -> list[base.Message]:
"""Handle document revisions from proponent"""
# Re-run discovery on updated documents
# Track revision history
pass
```
---
#### 10. Land Use Change Validation (Domain)
**Impact:** Missing validation for mandatory requirement (no land use change in past 10 years)
**Current Spec:** Only validates land tenure consistency, not land use history
**Required:**
```python
@mcp.tool()
async def validate_land_use_history(
session_id: str,
ctx: Context
) -> dict:
"""Verify no land use change in past 10 years"""
# Extract land use history from documents
# Check timestamped imagery (Sentinel, NDVI, Google Earth)
# Compare against 10-year threshold
# Return validation with evidence citations
pass
```
---
#### 11. Structured Error Handling (MCP Protocol)
**Impact:** Poor error messages, no recovery guidance
**Current Spec:** Basic error handling mentioned but not specified
**Required:**
```python
# src/registry_review_mcp/models/errors.py
from enum import Enum
from dataclasses import dataclass
class ErrorCategory(Enum):
CLIENT_ERROR = "client_error"
SERVER_ERROR = "server_error"
EXTERNAL_ERROR = "external_error"
class ErrorCode:
INVALID_SESSION = "invalid_session_id"
FILE_NOT_FOUND = "file_not_found"
PDF_EXTRACTION_FAILED = "pdf_extraction_failed"
# ... etc
@dataclass
class ReviewError(Exception):
category: ErrorCategory
code: str
message: str
details: dict | None = None
retry_after: int | None = None
# Usage in tools
def load_session(session_id: str) -> dict:
if not session_exists(session_id):
raise ReviewError(
category=ErrorCategory.CLIENT_ERROR,
code=ErrorCode.INVALID_SESSION,
message=f"Session {session_id} not found",
details={"suggestion": "Create session with /initialize first"}
)
```
---
#### 12. Comprehensive Logging (MCP Protocol)
**Impact:** Impossible to debug issues
**Current Spec:** Mentions logging but no patterns shown
**Required:**
```python
import structlog
logger = structlog.get_logger()
@mcp.tool()
async def discover_documents(
session_id: str,
ctx: Context[ServerSession, None]
) -> dict:
logger.info("discover_documents_started", session_id=session_id)
await ctx.info("Scanning document folder...")
try:
# ... processing ...
await ctx.report_progress(progress=i, total=total)
logger.info("discover_documents_completed",
session_id=session_id,
documents_found=len(documents))
return results
except Exception as e:
logger.error("discover_documents_failed",
session_id=session_id,
error=str(e),
exc_info=True)
await ctx.error(f"Discovery failed: {e}")
raise
```
---
#### 13. Context Type Annotations (MCP Protocol)
**Impact:** Type safety issues, unclear API
**Current Spec:** Shows `ctx: Context` without type parameters
**Required:**
```python
from mcp.server.fastmcp import Context
from mcp.server.session import ServerSession
async def discover_documents(
session_id: str,
ctx: Context[ServerSession, None] # Explicit typing
) -> dict:
pass
```
---
#### 14. Integration Test Specification (Implementation)
**Impact:** No way to verify MVP works
**Current Spec:** Lists expected behaviors but no assertions or test code
**Required:**
```python
# tests/test_integration.py
import pytest
from pathlib import Path
from mcp.client import Client
EXAMPLE_DATA = Path(__file__).parent.parent / "examples" / "22-23"
@pytest.mark.asyncio
async def test_botany_farm_workflow():
"""Complete workflow against example data"""
from registry_review_mcp.server import mcp
async with Client(mcp) as client:
# 1. Initialize
result = await client.call_tool("create_session", {
"project_name": "Botany Farm",
"documents_path": str(EXAMPLE_DATA),
"methodology": "soil-carbon-v1.2.2"
})
assert result["status"] == "initialized"
session_id = result["session_id"]
# 2. Document Discovery
docs = await client.call_tool("discover_documents", {
"session_id": session_id
})
assert docs["documents_found"] == 7
assert docs["classification_summary"]["project_plan"] == 1
# 3. Evidence Extraction
evidence = await client.call_tool("evidence_extraction", {
"session_id": session_id
})
assert evidence["requirements_mapped"] >= 18
# 4. Cross-Validation
validation = await client.call_tool("cross_validation", {
"session_id": session_id
})
assert validation["validations_passed"] >= 3
# 5. Report Generation
report = await client.call_tool("generate_review_report", {
"session_id": session_id,
"format": "markdown"
})
assert Path(report["report_path"]).exists()
# 6. Verify report content
report_text = Path(report["report_path"]).read_text()
assert "Botany Farm" in report_text
assert "C06-4997" in report_text
```
---
### 🟡 MEDIUM PRIORITY - Important for Production
#### 15. PDF Text Caching (Implementation)
**Impact:** Performance target (<60s for evidence extraction) is unrealistic without caching
**Current Spec:** Mentions caching (line 478) but never implements
**Required:**
```python
# src/registry_review_mcp/utils/cache.py
from pathlib import Path
import hashlib
import json
class PDFCache:
def __init__(self, cache_dir: Path):
self.cache_dir = cache_dir
self.cache_dir.mkdir(exist_ok=True)
def get_cache_key(self, filepath: Path) -> str:
stat = filepath.stat()
return hashlib.sha256(
f"{filepath}:{stat.st_mtime}:{stat.st_size}".encode()
).hexdigest()
def get(self, filepath: Path) -> dict | None:
key = self.get_cache_key(filepath)
cache_file = self.cache_dir / f"{key}.json"
if cache_file.exists():
return json.loads(cache_file.read_text())
return None
def set(self, filepath: Path, data: dict):
key = self.get_cache_key(filepath)
cache_file = self.cache_dir / f"{key}.json"
cache_file.write_text(json.dumps(data))
```
---
#### 16. State Management with Atomic Updates (Implementation)
**Impact:** Risk of corrupted session state from concurrent access
**Current Spec:** Mentions session.json but no file locking
**Required:**
```python
from contextlib import contextmanager
import fcntl
import json
@contextmanager
def atomic_session_update(session_path: Path):
"""Context manager for atomic session file updates"""
lock_file = session_path.with_suffix('.lock')
with open(lock_file, 'w') as lock:
fcntl.flock(lock.fileno(), fcntl.LOCK_EX)
try:
session = json.loads(session_path.read_text()) if session_path.exists() else {}
yield session
# Atomic write: temp file + rename
temp = session_path.with_suffix('.tmp')
temp.write_text(json.dumps(session, indent=2))
temp.rename(session_path)
finally:
fcntl.flock(lock.fileno(), fcntl.LOCK_UN)
# Usage
with atomic_session_update(session_path) as session:
session["status"] = "completed"
# Automatically saved on exit
```
---
#### 17. Name Variation Handling (Real-World Data)
**Impact:** False negatives on land tenure validation
**Evidence:** Actual review noted "different first names but same surname" for landowner
**Current Spec:** Tool 9 does exact string matching only
**Required:**
```python
from difflib import SequenceMatcher
@mcp.tool()
async def validate_name_consistency(
session_id: str,
name_fields: list[str],
fuzzy_match: bool = True,
ctx: Context
) -> dict:
"""Cross-check names with fuzzy matching"""
# Extract all names
# Try exact match first
# If fails, try:
# - Surname-only match
# - Initial + surname
# - 80%+ string similarity
# Flag for human review if ambiguous
pass
```
---
#### 18. Workflow Stage Alignment (Domain)
**Impact:** Confusion between spec stages and MVP user stories
**Current Spec:** 7 prompts vs. 8 user stories in MVP workflow spec
**Required:** Clarify relationship:
```markdown
## Workflow Stages vs User Stories
### MCP Prompts (User-Facing)
1. `/initialize` - Maps to Story 1 (Project Initialization)
2. `/document-discovery` - Maps to Story 2 (Document Discovery)
3. `/evidence-extraction` - Maps to Stories 3, 4, 5 combined:
- Story 3: Requirement Mapping
- Story 4: Completeness Check
- Story 5: Evidence Extraction
4. `/cross-validation` - Implicit in extraction
5. `/report-generation` - Maps to Story 6
6. `/human-review` - Maps to Story 7 (partial)
7. `/complete` - Finalization
### Implementation Tasks (Dev-Facing)
Story 8 (Commons Integration) is out of scope for MVP
```
---
#### 19. Realistic Performance Targets (Implementation)
**Impact:** Unrealistic expectations
**Current Spec:** Claims <60s for evidence extraction
**Revised Targets:**
```markdown
## Performance Targets (Revised)
### With Caching (Warm Run)
- Session creation: <2 seconds ✅
- Document discovery (7 files): <10 seconds ✅
- Evidence extraction (20 requirements): 60-90 seconds ⚠️
- PDF text extraction: ~10-15 seconds (cached after first run)
- Keyword search: ~5 seconds
- Evidence extraction: ~40-60 seconds
- Cross-validation: <10 seconds ✅
- Report generation: <5 seconds ✅
- **Total workflow (warm): 90-120 seconds**
### Without Caching (Cold Run)
- **Total workflow (cold): 2-3 minutes**
### For 70-Farm Batch (Phase 2)
- Sequential processing: 105-210 minutes
- Parallel processing (10 workers): 10-20 minutes
```
---
#### 20. Configuration Management (Implementation)
**Impact:** No way to override default paths or settings
**Current Spec:** Hardcodes paths
**Required:**
```python
# src/registry_review_mcp/config/settings.py
from pathlib import Path
import os
PROJECT_ROOT = Path(__file__).parent.parent.parent
DATA_DIR = Path(os.getenv("DATA_DIR", PROJECT_ROOT / "data"))
CHECKLISTS_DIR = DATA_DIR / "checklists"
SESSIONS_DIR = DATA_DIR / "sessions"
CACHE_DIR = DATA_DIR / "cache"
LOG_LEVEL = os.getenv("LOG_LEVEL", "INFO")
# Create directories
for dir_path in [CHECKLISTS_DIR, SESSIONS_DIR, CACHE_DIR]:
dir_path.mkdir(parents=True, exist_ok=True)
```
---
### 🟢 LOW PRIORITY - Nice to Have
#### 21. Parallel Document Processing
**Impact:** ~2x speedup for discovery/extraction
**Current Spec:** Sequential processing
**Future Enhancement:**
```python
import asyncio
async def discover_documents_parallel(session_id: str, ctx: Context) -> dict:
files = scan_directory(documents_path)
# Process up to 5 PDFs in parallel
semaphore = asyncio.Semaphore(5)
async def process_one(file):
async with semaphore:
return await classify_and_extract(file, ctx)
results = await asyncio.gather(*[process_one(f) for f in files])
return aggregate_results(results)
```
---
#### 22. Secondary Reviewer Workflow (Domain)
**Impact:** May not satisfy governance requirements
**Evidence:** Transcripts mention "secondary review by team member"
**Future Enhancement:**
```python
class Session(BaseModel):
# ... existing fields ...
primary_reviewer: str | None = None
secondary_reviewer: str | None = None
primary_review_completed: bool = False
secondary_review_completed: bool = False
```
---
#### 23. Crediting Period Validation (Domain)
**Impact:** May miss common date errors
**Current Spec:** Extracts crediting_period but doesn't validate
**Future Enhancement:**
```python
@mcp.tool()
async def validate_crediting_period(session_id: str, ctx: Context) -> dict:
"""Validate crediting period business rules"""
# Rules:
# - Must be 10-40 years
# - Start date ≤ project start date
# - End date consistent across documents (±30 days)
# - Monitoring frequency matches protocol
pass
```
---
## Findings by Category
### Domain Accuracy (Regen Registry Process)
**Excellent Alignment:**
- ✅ Core pain points correctly identified (document organization, cross-checking)
- ✅ Human-AI collaboration philosophy matches vision
- ✅ Evidence traceability principles sound
**Missing/Incorrect:**
- ❌ Batch processing (Critical - primary use case)
- ❌ SharePoint integration (High - current source)
- ❌ Proponent correction loops (High - common scenario)
- ❌ Land use change validation (High - mandatory requirement)
- ⚠️ Time savings estimates overly optimistic without batch support
---
### Real-World Data Compatibility
**What Works:**
- ✅ PDF text extraction approach
- ✅ Filename pattern classification
- ✅ Basic cross-validation logic
**Critical Gaps:**
- ❌ GIS file handling (3 requirements blocked)
- ❌ Structured field extraction (5 requirements blocked)
- ❌ Legal document parsing (attestations, deeds)
- ❌ Temporal data validation (leakage requirement)
- ⚠️ Multi-source evidence aggregation (4 requirements affected)
**Estimated Success Rate:** 60% of requirements can be auto-populated with current spec
---
### MCP Protocol Compliance
**Strengths:**
- ✅ Excellent Prompts > Tools > Resources hierarchy
- ✅ Tools are properly atomic and composable
- ✅ Prompts effectively guide workflows
**Gaps:**
- ❌ Missing `/list-capabilities` discovery prompt
- ⚠️ Context type annotations incomplete
- ⚠️ Error handling not structured
- ⚠️ Logging patterns not specified
- ⚠️ Resource access patterns unclear
**Overall Grade:** B+ (Good with critical gaps)
---
### Implementation Readiness
**Architecture:** A- (Strong design)
**Specifications:** C (30-40% complete for implementation)
**Critical Missing:**
- ❌ Server entry point (server.py)
- ❌ Concrete tool implementations
- ❌ Complete pyproject.toml
- ❌ Integration test with assertions
- ❌ Example checklist JSON data
- ❌ Infrastructure code (logging, config, errors, cache)
**Estimated Time to Implementation-Ready:** 2-3 days of spec work
---
## Recommended Action Plan
### Phase 0: Specification Completion (2-3 days)
**Day 1: Critical Infrastructure**
1. ✅ Fix pyproject.toml syntax
2. ✅ Create complete server.py with tool/prompt registration
3. ✅ Specify logging setup (stderr requirement)
4. ✅ Define error hierarchy and handling patterns
5. ✅ Create example checklist JSON from examples/checklist.md
6. ✅ Add `/list-capabilities` prompt
**Day 2: Core Tools Implementation Specs**
1. ✅ Complete implementation of `extract_pdf_text` with caching
2. ✅ Complete implementation of `create_session` with state management
3. ✅ Add GIS file handling tools
4. ✅ Add structured field extraction tool
5. ✅ Add configuration management module
**Day 3: Testing & Documentation**
1. ✅ Write complete integration test with assertions
2. ✅ Add development setup guide with troubleshooting
3. ✅ Document batch processing strategy (even if Phase 2)
4. ✅ Clarify SharePoint workaround or integration plan
5. ✅ Revise performance targets with caching assumptions
---
### Phase 1: MVP Implementation (3-4 weeks)
**Week 1: Infrastructure**
- Logging, configuration, errors, state management
- Test framework setup
- Example data preparation
**Week 2: Core Tools**
- Session management
- Document discovery (PDF + GIS)
- PDF text extraction with caching
**Week 3: Evidence Tools**
- Structured field extraction
- Requirement mapping
- Evidence extraction
- Basic validations
**Week 4: Workflows & Integration**
- Implement all 7 prompts
- End-to-end testing against examples/22-23
- Claude Code integration testing
- Documentation
---
### Phase 2: Production Features (2-3 weeks)
**Enhanced Validation:**
- Land use change validation
- Crediting period rules
- Name variation handling
**Batch Processing:**
- Batch session creation
- Parallel processing
- Aggregated reporting
**Data Connectors:**
- SharePoint read-only integration (Microsoft Graph)
- Google Drive connector (stretch)
---
## Positive Findings
Despite the gaps, the specification demonstrates excellent work in several areas:
✅ **Strong Architectural Vision**
- Prompts > Tools > Resources hierarchy correctly implemented
- Clear separation of concerns
- Human-AI collaboration philosophy well-articulated
✅ **Good Domain Understanding**
- Core pain points accurately identified
- Evidence traceability principles sound
- Fail-explicit design philosophy appropriate
✅ **Well-Structured Workflows**
- Seven sequential prompts cover complete review lifecycle
- Tool composition in prompts demonstrates MCP best practices
- User experience flow is logical and guided
✅ **Comprehensive Data Models**
- Pydantic models in Appendix A are well-designed
- JSON schemas properly specified
- Resource structures are sound
✅ **Thoughtful Extensibility**
- Clear phase breakdown for future features
- Plugin points for additional methodologies
- Migration paths identified
---
## Conclusion
The specification is **architecturally excellent but implementation-incomplete**. It demonstrates strong understanding of both the Regen Registry domain and MCP protocol design principles. The workflow decomposition is sound, the tool boundaries are appropriate, and the human-AI collaboration model is well-conceived.
However, critical implementation details are missing:
- **30% domain completeness** - Missing batch processing, SharePoint, corrections
- **60% real-world data completeness** - Missing GIS, structured fields, legal docs
- **75% MCP protocol completeness** - Missing discovery, logging, error patterns
- **40% implementation completeness** - Missing concrete code, tests, configuration
**Recommendation**: Invest 2-3 days in specification completion before beginning implementation. The architectural foundation is strong enough that these additions will slot in cleanly without requiring redesign.
**Overall Assessment**: B+ specification that becomes A- after addressing Critical and High Priority items.
---
**Document Version:** 1.0
**Review Completed:** November 11, 2025
**Next Review:** After specification revisions
