MCP Tools Overview

Once you’ve connected ACECode as an MCP server, your AI assistant gains access to the tools listed below. Each tool is purpose-built for a specific code-intelligence task — together they cover search, code graph, git history, project metadata, and more.

Code discovery (4 grouped tools)

These four tools cover ~80% of what you’ll ask ACE to do. Each has multiple modes — pick the mode that matches your intent.

Modes: search, symbols
Semantic + keyword hybrid search. Finds code by meaning, auto-bundles pattern matches and symbol maps for top results. Use this for “where is X” and “how does Y work”.

graph

Modes: relationships, impact, flow
Dependency graph. “What depends on AuthService?” / “What breaks if I change this?” / “Trace the call chain from POST /login.”

history

Modes: lineage, evolution, diff
Git intelligence. Commit search, weekly digests, blast radius of a diff. Use this for “when did this change and why?”

Specialised tools

Tool	Purpose
`files`	List indexed files, filter by path or language
`projects`	Register / list / get status / remove projects
`index`	Queue a re-indexing job
`review`	AI code review on a diff
`validate`	Hallucination check — verify a symbol or import exists in the index
`logic`	Business rules, state machines, call flows
`docs`	Search the library-docs knowledge base (npm, PyPI, crates.io, Go)
`enrich`	Prompt enrichment pipeline (used by the `/ace enrich` skill)
`list-skills`	Discover available enrich modes
`recall`	Semantic memory recall — search across past sessions
`remember`	Save a memory the assistant should recall in future sessions
`recap`	Compress a long session into anchor memories
`my_skills`	Runtime access to your custom + generated skills
`my_agents`	Runtime access to your custom agents
`my_prompts`	Back-compat alias for skills with `tier=custom activation=manual`

Tool-selection cheat sheet

# Find code by meaning
search { query: "how does auth work", project: "my-project" }

# Symbol definitions
search { query: "Repository", project: "my-project", mode: "symbols", symbolType: "class" }

# Map dependencies before refactoring
graph { query: "AuthService", project: "my-project", mode: "relationships" }

# Blast radius — what breaks if I change this?
graph { query: "AuthService", project: "my-project", mode: "impact", depth: 3 }

# Trace a call chain from an entry point
graph { query: "POST /login", project: "my-project", mode: "flow" }

# Why does this file look the way it does?
history { query: "src/auth.ts", project: "my-project", mode: "lineage" }

# Recent activity digest
history { query: "last week", project: "my-project", mode: "evolution" }

# Architecture overview
meta { project: "my-project", mode: "architecture" }

# Project conventions and gotchas
meta { query: "auth patterns", project: "my-project", mode: "memories" }

Multilingual queries

ACECode’s embeddings (Voyage voyage-4-large) and reranker (xAI grok-4.3) are both multilingual. You can query in Vietnamese, Chinese, Japanese, or mixed languages without pre-translating. The pipeline matches the query embedding directly against the (English) code index.

# These work natively:
search { query: "tìm hàm xử lý đăng nhập" }
search { query: "认证中间件在哪里" }

Pre-translate only if results look off for an unusually idiomatic phrase.

Per-tool reference

Coming in Phase 2: a dedicated page per tool with full parameter schema, return shape, latency budget, and credit cost. For now, the API reference endpoint returns the live JSON Schema for every tool.