Repository intelligence

jumodada/Drissionpage-MCP-Server

GitHub

DrissionPage MCP Server · Browser automation for Claude Code, Codex, and MCP clients

CLOUDM0N decision
REVIEW BEFORE ADOPTION
Trust REVIEW · 90/100
Good fit if

Teams whose requirements match this repository’s core capability.

Watch out for

Review deployment and security evidence before production adoption.

Practical intelligence

What matters before you adopt it

Best for
Teams whose requirements match this repository’s core capability.
Main trade-offs
Review deployment and security evidence before production adoption.
Trust & CVEs

Security evidence without the noise

Trust remains a decision signal; CVEs and scanner evidence explain what is driving the risk.

Security findings
1
CLOUDM0N scanner findings
Critical
0
High
0
Medium
1
Low
0
View trust evidence & security findings
Why this score
No trust rationale was stored for this scan.
CLOUDM0N findings
MEDIUM
The project can spawn operating-system processes; review command construction and input handling. 2 sample match(es) found.
Architecture from code6 modules · 3 edges
Structural evidence

Modules and dependency edges extracted from repository code. This is code evidence, not README inference.

Code files
125
Modules
6
Dependency edges
3
Core modules
(root)
1 files
drissionpage_mcp
71 files
playground
6 files
Dependency flow
playgrounddrissionpage_mcp
Detected languages
Python
Detected frameworks
Pydantic
Architecture evidence details
flowchart TD
    %% drissionpage-mcp — high-level architecture (DRAFT, refine me)
    n0["(root) · 1 file"]
    n1["drissionpage_mcp · 71 files"]
    n2["playground · 6 files"]
    n3["tests · tests · 47 files"]
    n2 --> n1
    n3 --> n1
    n3 --> n2
    class n3 test
    classDef test fill:#499894,color:#ffffff,stroke:#397975
Agent handoff
Use with any agent
JSON API
Alternatives

Nearby repositories worth comparing before adoption.

Compare top options →
codebase-memory-mcp
DeusData/codebase-memory-mcp
71
Fit

This MCP server transforms how developers interact with codebases by building a persistent knowledge graph that indexes repositories in milliseconds across 155 programming languages. With sub-millisecond query speeds and 99% token reduction, it enables AI coding assistants like Cursor, Claude Code, and Windsurf to understand your entire codebase context without drowning in context windows. Built as a single static binary with zero dependencies, it runs anywhere.

Trust REVIEW · 55
Compare →
jcodemunch-mcp
jgravelle/jcodemunch-mcp
17
Fit

jcodemunch-mcp is the ultimate token-saver for AI-powered code exploration! By leveraging tree-sitter AST parsing, this MCP server lets you dive deep into GitHub repositories without burning through your token budget. Built for developers who want smarter, leaner AI interactions with source code—perfect for code review, refactoring analysis, and understanding unfamiliar codebases fast.

Trust FAIL · 25
Compare →
graphify
Graphify-Labs/graphify
74
Fit

Turn any codebase, with its docs, SQL schemas, configs, and PDFs, into a queryable knowledge graph. A /graphify skill for Claude Code, Cursor, Codex, and Gemini CLI: local deterministic AST parsing, every edge explained, no vector store.

Trust REVIEW · 45
Compare →