Repository Analysis

exa-labs/exa-mcp-server

Exa MCP for web search and web crawling!

3.8 Likely human-written View on GitHub

Analysis Overview

This report presents the forensic synthetic code analysis of exa-labs/exa-mcp-server, a TypeScript project with 4,717 GitHub stars. SynthScan v2.0 examined 28,492 lines of code across 76 source files, recording 46 pattern matches distributed across 6 syntactic categories. The overall adjusted score of 3.8 places this repository in the Likely human-written band.

The scanner applied 160+ deterministic lexical heuristics, multi-line block detectors, abstract syntax tree depth profilers, and a cross-file Jaccard similarity matrix to construct a statistically normalised synthetic code estimate. All matches are individually weighted by severity coefficient and contextual multiplier before summation, and the resulting headline score is temporally discounted to account for the repository's development history relative to the commercial emergence of large language model coding tooling (November 2022 onward).

3.8
Adjusted Score
3.8
Raw Score
100%
Time Factor
2026-07-14
Last Push
4.7K
Stars
TypeScript
Language
28.5K
Lines of Code
76
Files
46
Pattern Hits
2026-07-14
Scan Date
0.17
HC Hit Rate

What These Metrics Mean

Adjusted Score
Primary synthetic code indicator. Raw score normalised per 1,000 lines of code and multiplied by the temporal discount factor. This is the definitive comparative metric — use it to rank repositories by AI authorship density.
Raw Score
The unmodified sum of all severity-weighted, context-multiplied pattern match scores before temporal discounting. Reflects the absolute signal strength independent of when the repository was last active.
Time Factor
The temporal discount multiplier (0–100%) applied to the raw score. Repositories last updated before ChatGPT's launch (Nov 2022) receive a 5% factor. Full signal is only assigned to repositories active in the post-adoption era (Jan 2024+).
Pattern Hits
Total count of individual pattern matches across all files and categories. A high hit count with a low score may indicate a very large codebase with isolated AI snippets; a low count with a high score indicates dense, concentrated AI signatures.
HC Hit Rate
High+Critical pattern hits per file, averaged across the repository. This orthogonal signal catches repositories where a few files are densely packed with high-severity AI tells — a strong indicator even when the normalised score appears moderate due to codebase size.
Lines of Code / Files
Total lines and files analysed. The scanner examines 94 file extensions. These denominators are used to normalise the score, enabling fair comparison between repositories of vastly different sizes.

Score History

Longitudinal tracking requires multiple scan runs. Once this repository is re-scanned after new commits land, this chart will visualise how the synthetic code signal evolves over time — enabling you to detect whether AI authorship is growing, stabilising, or being actively corrected by human engineers.

No multi-scan history yet — run the scanner again to build trend data.

Severity Breakdown

Classifies detected patterns by their diagnostic confidence and structural impact. CRITICAL patterns (coefficient 10) represent definitive synthetic signatures — hallucinated imports, explicit LLM attribution metadata — virtually never produced by human authors. HIGH (5) indicates strong structural tells such as cross-file repetition or cross-linguistic idioms. MEDIUM (2) covers recognisable conversational padding and AI-specific vocabulary. LOW (1) captures subtle indicators like tautological comments and generic boilerplate that require density to carry independent signal.

CRITICAL 0HIGH 13MEDIUM 7LOW 26

Directory Score Breakdown

This horizontal bar chart decomposes the repository's raw synthetic code score by top-level directory, allowing you to pinpoint precisely which modules or components carry the highest AI authorship density. Directories with disproportionately high scores relative to their size warrant targeted manual review: concentrated AI signatures often trace back to mass-generated configuration layers, auto-ported test suites, LLM-scaffolded boilerplate classes, or entire subsystems authored under heavy copilot assistance. Use this view to prioritise your human code-review effort.

Pattern Findings

The scanner identified 46 distinct pattern matches across 6 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a statistically significant AI authorship indicator. Expand any category row to inspect the individual file paths, line numbers, code snippets, and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.

Reading the findings table: The Severity column indicates the diagnostic confidence level (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — comment-context matches receive a ×1.5 weight because LLMs systematically over-annotate. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier as dense clusters constitute far stronger evidence of synthetic authorship than isolated hits.

Magic Placeholder Names13 hits · 65 pts
SeverityFileLineSnippetContext
HIGHnpm.readme.md25 "EXA_API_KEY": "your_api_key"CODE
HIGHnpm.readme.md45 "EXA_API_KEY": "your_api_key"CODE
HIGHnpm.readme.md57claude mcp add --transport stdio --env EXA_API_KEY=your_api_key exa -- npx -y exa-mcp-serverCODE
HIGHnpm.readme.md75 "EXA_API_KEY": "your_api_key"CODE
HIGHnpm.readme.md87codex mcp add --env EXA_API_KEY=your_api_key exa -- npx -y exa-mcp-serverCODE
HIGHnpm.readme.md103 "EXA_API_KEY": "your_api_key"CODE
HIGHnpm.readme.md124 "EXA_API_KEY": "your_api_key"CODE
HIGHnpm.readme.md145 "EXA_API_KEY": "your_api_key"CODE
HIGHnpm.readme.md165 "EXA_API_KEY": "your_api_key"CODE
HIGHnpm.readme.md185 "EXA_API_KEY": "your_api_key"CODE
HIGHnpm.readme.md205 "EXA_API_KEY": "your_api_key"CODE
HIGHREADME.md304 "EXA_API_KEY": "your_api_key"CODE
HIGHllm_mcp_docs.txt4068 "GITHUB_PERSONAL_ACCESS_TOKEN": "<YOUR_TOKEN>"CODE
Hyper-Verbose Identifiers15 hits · 15 pts
SeverityFileLineSnippetContext
LOWsrc/toolRegistry.ts134export function requiresUserProvidedApiKey(toolId: ToolId): boolean {CODE
LOWsrc/tools/validation.ts25export function lenientOptionalPositiveNumber() {CODE
LOWsrc/tools/agentCreateRun.ts21export function registerAgentCreateRunTool(server: McpServer, config?: AgentToolConfig): void {CODE
LOWsrc/tools/agentWaitForRun.ts43export function registerAgentWaitForRunTool(server: McpServer, config?: AgentToolConfig): void {CODE
LOWsrc/tools/agentCancelRun.ts9export function registerAgentCancelRunTool(server: McpServer, config?: AgentToolConfig): void {CODE
LOWsrc/tools/linkedInSearch.ts11export function registerLinkedInSearchTool(server: McpServer, config?: { exaApiKey?: string; userProvidedApiKey?: booleaCODE
LOWsrc/tools/webSearchAdvanced.ts11export function registerWebSearchAdvancedTool(server: McpServer, config?: { exaApiKey?: string; userProvidedApiKey?: booCODE
LOWsrc/tools/companyResearch.ts11export function registerCompanyResearchTool(server: McpServer, config?: { exaApiKey?: string; userProvidedApiKey?: booleCODE
LOWsrc/tools/deepResearchStart.ts10export function registerDeepResearchStartTool(server: McpServer, config?: { exaApiKey?: string; userProvidedApiKey?: booCODE
LOWsrc/tools/deepResearchCheck.ts15export function registerDeepResearchCheckTool(server: McpServer, config?: { exaApiKey?: string; userProvidedApiKey?: booCODE
LOWsrc/tools/agentGetRunOutput.ts10export function registerAgentGetRunOutputTool(server: McpServer, config?: AgentToolConfig): void {CODE
LOWsrc/utils/exaResponseSanitizer.ts286export function sanitizeDeepSearchStructuredResponse(response: ExaDeepSearchResponse | unknown): Record<string, unknown>CODE
LOWsrc/utils/mcpClientMetadata.ts78export function extractInitializeClientInfo(body: string | undefined): McpClientInfo | undefined {CODE
LOWsrc/utils/mcpClientMetadata.ts99export function sanitizeMcpClientMetadata(metadata: unknown): McpClientMetadata | undefined {CODE
LOWsrc/utils/mcpClientMetadata.ts137export function serializeMcpClientMetadata(value: unknown): string | undefined {CODE
Modern AI Meta-Vocabulary6 hits · 12 pts
SeverityFileLineSnippetContext
MEDIUMllm_mcp_docs.txt247[Amazon Q CLI](https://github.com/aws/amazon-q-developer-cli) is an open-source, agentic coding assistant for terminals.CODE
MEDIUMllm_mcp_docs.txt288[BeeAI Framework](https://i-am-bee.github.io/beeai-framework) is an open-source framework for building, deploying, and sCODE
MEDIUMllm_mcp_docs.txt819[VS Code](https://code.visualstudio.com/) integrates MCP with GitHub Copilot through [agent mode](https://code.visualstuCODE
MEDIUMllm_mcp_docs.txt831[Warp](https://www.warp.dev/) is the intelligent terminal with AI and your dev team's knowledge built-in. With natural lCODE
MEDIUMllm_mcp_docs.txt855[Windsurf Editor](https://codeium.com/windsurf) is an agentic IDE that combines AI assistance with developer workflows. CODE
MEDIUMllm_mcp_docs.txt888[Zencoder](https://zecoder.ai) is a coding agent that's available as an extension for VS Code and JetBrains family of IDCODE
Excessive Try-Catch Wrapping8 hits · 10 pts
SeverityFileLineSnippetContext
LOWllm_mcp_docs.txt2671 except Exception as error:CODE
LOWllm_mcp_docs.txt3309 except Exception as exc:CODE
LOWllm_mcp_docs.txt3375 except Exception as exc:CODE
LOWllm_mcp_docs.txt3384 except Exception as exc:CODE
LOWllm_mcp_docs.txt3391 except Exception as exc:CODE
LOWllm_mcp_docs.txt4578 except Exception as e:CODE
LOWllm_mcp_docs.txt6121 except Exception:CODE
MEDIUMllm_mcp_docs.txt3370def message_handler():CODE
Structural Annotation Overuse3 hits · 4 pts
SeverityFileLineSnippetContext
LOWskills/search/SKILL.md24## Step 1: Assess the QueryCOMMENT
LOWskills/search/SKILL.md65## Step 2: Dispatch SubagentsCOMMENT
LOWskills/search/SKILL.md142## Step 3: Compile ResultsCOMMENT
Overly Generic Function Names1 hit · 1 pts
SeverityFileLineSnippetContext
LOWapi/mcp.ts580async function handleRequest(request: Request, options?: { forceOAuth?: boolean }): Promise<Response> {CODE