Token Pilot MCP server

Read from the package source without running it. The installed server may list more.

• call_tree

  Recursive depth-N call hierarchy for a function. Shows who calls who transitively — complements find_usages (flat one-level refs) by revealing full chains from leaf helpers to entry points. Use for debugging, refactor impact, and verifying reachability.

• code_audit

  Find code quality issues: TODO/FIXME comments, deprecated symbols, structural code patterns (bare except:, print() calls). Use for project-wide audits.

• explore

  One-shot ranked context + call/inheritance graph blast-radius for a query. Returns ranked symbols, the source heads of the top-ranked files, graph neighbours (callers + subclasses — the blast radius), and related test files in a single compact block. Use INSTEAD OF separate find_usages + read_symbol + call_tree when you need to understand an area fast — cheaper than chaining those three.

• explore_area

  One-call exploration of a directory: outline (all symbols), imports (external deps + who imports this area), tests (matching test files), recent git changes. Use INSTEAD OF separate outline + related_files + git log calls. Default since v0.30.0 returns only outline+changes — telemetry showed the all-4 default producing negative token reduction for small areas. Opt into imports/tests explicitly via

• find_unused

  Find dead code — functions, classes, and variables with no references across the project. Use for cleanup and refactoring.

• find_usages

  Use INSTEAD OF Grep for finding symbol references. Semantic search — groups by: definitions, imports, usages. Supports scope, kind, limit, lang filters. Use context_lines to include surrounding code. HINT: for very short / generic symbols (≤4 chars like `id`, `err`, `Cmd`, `db`) Grep is usually cheaper than find_usages — the semantic grouping doesn't pay off when the symbol resolves ambiguously ac

• module_info

  Analyze module dependencies, dependents, public API, and unused deps. Use for architecture understanding and dependency cleanup.

• module_route

  Show the transitive dependency path(s) between two modules — how module A reaches module B through the import graph. Use to answer 'how does X depend on Y?', trace coupling, or generate a dependency diagram. format='mermaid'/'dot' emits a diagram; default text lists the hops.

• outline

  Use INSTEAD OF listing dir + reading each file. One call returns all symbols (classes, functions, methods, routes) for every code file in a directory. Supports recursive with max_depth.

• project_overview

  START HERE for unfamiliar codebases. Shows project type, architecture, framework detection, quality tools, CI, directory map. Use include filter for specific sections.

• read_diff

  Use INSTEAD OF re-reading whole file after edits. Shows only changed hunks. REQUIRES: call smart_read or read_for_edit BEFORE editing to create baseline snapshot.

• read_for_edit

  Use INSTEAD OF Read when preparing an EDIT. Returns exact RAW code around a symbol or line — copy directly as old_string for Edit tool. Supports batch: pass "symbols" array to get multiple edit contexts in one call. Unlike read_symbols (for reading/understanding), this returns unformatted code optimized for copy-paste into Edit. Optional: include_callers, include_tests, include_changes for enriche

• read_range

  Read a specific line range from a file. Use when you know exact lines — lighter than reading the whole file.

• read_section

  Read a specific section from Markdown, YAML, JSON, or CSV files. Markdown: by heading name. YAML/JSON: by top-level key. CSV: by row range (rows:1-50). Much cheaper than reading the whole file. DOCS/DATA ONLY — `heading` is required; this does NOT read code by line/symbol. For source files use read_range (line range) or read_symbol (one symbol).

• read_symbol

  Read source code of ONE specific function/method/class — INSTEAD OF reading the whole file. Supports Class.method syntax.

• read_symbols

  Batch read MULTIPLE symbols from ONE file — saves N-1 round-trips vs calling read_symbol N times. BEST FIT: 3–8 symbols in one file when you need their bodies. For 1–2 symbols use read_symbol (simpler). If you'd request ≥70% of the file's symbols, the handler refuses and points you to smart_read — that's cheaper than a large batch. For edit preparation use read_for_edit.

• related_files

  Show ranked import graph for a file: imports, importers, and tests scored by relevance (test adjacency, import closeness, recent changes, path proximity). Files ranked into HIGH VALUE / MEDIUM / LOW to prioritize reading.

• session_analytics

  Show token savings report: calls, tokens saved, per-tool breakdown, top files, cache hits. Use verbose=true for full breakdown (per-intent, decision insights, savings by category).

• session_budget

  META / info-only: reports Read-hook pressure for this session (suppressed tokens, reference budget, burn fraction, effective denyThreshold). Does NOT save tokens itself — this is diagnostic, use to decide when to tighten before a big read. NOTE: burnFraction measures hook activity, not actual context-window occupancy.

• session_snapshot

  Capture current session state as a compact markdown block (<200 tokens). Call before compaction, when switching direction, or periodically in long sessions. Model provides the facts, tool formats them.

• smart_diff

  Use INSTEAD OF raw git diff. Shows changed files with AST symbol mapping — which functions/classes were modified/added/removed. Small diffs include hunks, large diffs show summary.

• smart_log

  Use INSTEAD OF raw git log. Structured commit history with category detection (feat/fix/refactor/docs), file stats, author breakdown. Filters by path and ref. HEADS UP: two verification runs measured this tool at ~39% token reduction (borderline — vs 95-99% for outline/smart_diff). Cumulative data being gathered — tool may be dropped or redesigned in v0.30.0 if numbers don't improve. Prefer scopin

• smart_read

  Use INSTEAD OF Read/cat for code files. Returns code structure (classes, functions, methods with signatures and line ranges) — 60-80% fewer tokens than raw content. Use read_symbol() to drill into specific code.

• smart_read_many

  Batch smart_read for multiple files at once — INSTEAD OF calling Read on each file. Returns structure for each file. Max 20 files.

• test_summarywrite action

  Run tests and return structured summary: total/passed/failed/skipped + failure details. 200 lines of raw output → 10-15 lines. Supports vitest, jest, pytest, phpunit, go test, cargo test.

• Code scan236 source files scanned15/25
• –Live reliabilityno gateway calls yet and no remote to proben/a
• –Tool poisoningtools not inspected (local package is not executed); not countedn/a
• Auth qualitylocal package, no credentials required12/15
• Maintenancelast push 6 days ago15/15
• Maintainer identityregistry namespace matches repository owner; GitHub account older than a year9/10

Token Pilot: common questions

Is Token Pilot MCP server safe?

Mostly: it is graded B (78/100). Read the Token Pilot safety report

How do I install Token Pilot?

It runs on your machine. Copy the Claude Code, Claude Desktop or Cursor config from the install section.

Does Token Pilot need an API key?

Not as far as the registry entry and our scan can tell: no credentials are declared or required.

Is Token Pilot maintained?

The last commit was 7 days ago (2026-09-13). The latest release is v0.52.1.

What can I use instead of Token Pilot?

Servers from other publishers that do the same job: jCodemunch MCP server.