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Pharaoh-so

Pharaoh

by Pharaoh-so

Pharaoh

Codebase intelligence for AI agents. Your AI understands your architecture before it writes a single line.

Pharaoh MCP server

pharaoh.so


Quick Start (60 seconds)

Claude Code

claude mcp add pharaoh --transport sse https://mcp.pharaoh.so/sse

Cursor

Add to .cursor/mcp.json:

{
  "mcpServers": {
    "pharaoh": {
      "url": "https://mcp.pharaoh.so/sse"
    }
  }
}

Generic MCP Client

{
  "mcpServers": {
    "pharaoh": {
      "transport": "sse",
      "url": "https://mcp.pharaoh.so/sse"
    }
  }
}

Setup

  1. Add the MCP URL to your client (see above)

  2. Authorize via OAuth — you'll be prompted to install the Pharaoh GitHub App on your org

  3. Repos are mapped automatically. Start querying.


What Pharaoh Does

Pharaoh parses your repositories using tree-sitter into a Neo4j knowledge graph — functions, modules, imports, exports, call chains, endpoints, complexity scores, all mapped as nodes and edges. AI agents query the graph via MCP for structured architectural context instead of reading files one at a time. Deterministic analysis — no LLM in the pipeline, zero hallucination risk.


Tools

Tool

What it does

Tier

get_codebase_map

Full structural overview — modules, dependency graph, entry points, hot files

Free

get_module_context

Complete module profile — functions, exports, internal deps, complexity scores

Free

search_functions

Find existing functions before writing new ones — name, signature, location, callers

Free

get_blast_radius

Trace all downstream callers up to 5 hops before refactoring

Free

query_dependencies

Forward, reverse, and circular dependency tracing between modules

Free

check_reachability

Verify exports are wired to production entry points

Pro

get_regression_risk

Score functions by complexity, exposure, churn, and caller count

Pro

get_unused_code

Graph-based dead code detection with text-reference backup

Pro

get_consolidation_opportunities

Detect duplicate logic, parallel consumers, signature twins

Pro

get_test_coverage

Per-module coverage with untested high-complexity function flagging

Pro

get_vision_docs

Cross-reference PRDs and specs against implementation

Pro

get_vision_gaps

Find specs without code and complex code without specs

Pro

get_cross_repo_audit

Compare two repositories for structural duplication and drift

Pro


Example Session

You: "What breaks if I rename formatMessage?"

Pharaoh → get_blast_radius
  Risk: HIGH
  Direct callers: 4 (across 3 modules)
  Transitive impact: 12 functions
  Affected endpoints: POST /api/notifications/send, POST /api/slack/webhook
  Affected cron: daily-digest (09:00 UTC)

You: "Is there already a retry wrapper?"

Pharaoh → search_functions
  Found: withRetry() in src/utils/resilience.ts:42
  Exported: yes | Async: yes | Complexity: 8
  Used by 6 callers across 3 modules
  → Agent imports existing function instead of writing a new one.

How It Works

  • Tree-sitter parsing (deterministic, no LLM) into a Neo4j knowledge graph

  • GitHub webhook auto-refreshes on every push to default branch

  • ~60 seconds to map a 50K LOC TypeScript project

  • Structural metadata only — no source code stored


FAQ

Does Pharaoh store my source code? No. The graph contains function names, file paths, dependency relationships, complexity scores, and export signatures. Never source code.

What languages are supported? TypeScript and Python today. Tree-sitter makes adding languages straightforward.

How does it stay current? GitHub webhook fires on every push. Your graph is always up to date.

Can I use it with private repos? Yes. Read-only access via the GitHub App. Tenant-isolated — your data is never visible to other customers.

How is this different from Sourcegraph / CodeScene / SonarQube? Sourcegraph answers "where is it?" — text search across repos. CodeScene analyzes behavioral patterns from git history. SonarQube does line-level static analysis and linting. Pharaoh answers "what breaks if I change this?" — structural and architectural intelligence built for AI agents, not dashboards.


Built by a dev who got tired of AI agents breaking things they couldn't see.

-
security - not tested
-
license - not tested
-
quality - not tested

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