WaveScope MCP

Wavelet-based multi-resolution context management for LLMs via MCP.

Provides a zoomable view of code files — the model can look at high-level structure, then drill down to specific regions as needed, without loading entire files into context.

How it works

1. Structural signal — each line gets an importance score based on indentation, keywords (class, def, export, etc.), and comment status.

2. Ricker wavelet transform — the signal is convolved with Ricker (Mexican hat) wavelets at 8 scales (1–128), detecting structural boundaries at multiple resolutions.

3. Multi-scale peaks — coefficient maxima are extracted and sorted by magnitude, identifying the most important structural transitions.

4. Band assembly — three zoom levels, sized as a fraction of the query radius (default 300):

   • Fine (scales 1–2): raw lines in ±radius/5 (≥10 lines)
   • Medium (scales 4–16): function/class signatures in ±radius/2
   • Coarse (scales 32–128): section-level structural summary across ±radius

Installation

From npm (recommended)

npm install -g wavescope-mcp
# or locally in a project:
npm install wavescope-mcp

From source

git clone <repo-url>
cd wavescope-mcp
pnpm install    # auto-builds dist/ via prepare script

Usage

Running as MCP server

After global install, just use the binary name:

{
  "mcpServers": {
    "wavescope": {
      "command": "wavescope-mcp"
    }
  }
}

With a local install, use npx:

{
  "mcpServers": {
    "wavescope": {
      "command": "npx",
      "args": ["wavescope-mcp"]
    }
  }
}

Tools

query_wavelet_context

Multi-resolution view around a position.

• file — absolute path to the file
• center — line number (0-indexed)
• radius — total range to consider, 10–2000 (default 300)

Returns center, clamped (and clampedFrom when out of range was clamped), three fine/medium/coarse bands, and detected wavelet peaks.

get_important_positions

Find structural boundaries (class/function defs, imports, etc.).

• exactly one of file (single file path) or directory (project-wide search)
• min_coefficient — raw wavelet coefficient threshold, 0–20 (default 0.3). Same semantics in both single-file and project mode. Typical useful range is 0.1–3; the upper bound is generous because CWT coefficients can exceed 2 at large scales.
• limit — max results, 1–100 (default 20)

get_wavelet_coefficients

Raw wavelet coefficients for custom analysis.

• file, start, end, scale (required, 1–128)

Returned object includes scale (the actual scale used) and requestedScale (the original scale you asked for) — they differ when the requested scale isn't in the index and the nearest available one is substituted. The result also carries clamped (true if the requested start/end were adjusted to fit the valid coefficient range) and clampedFrom: {start, end} (the original values, present only when clamped is true). A range entirely outside the file returns coefficients: [] with clamped: true rather than fabricating a boundary value.

get_summary_at_scale

Compressed view of a region using specified scale peaks.

• file, start, end, scale (optional — auto-selected based on region size if omitted: ≤50 lines → 2, ≤200 → 8, ≤800 → 32, >800 → 128)

diff_wavelet_context

Compare structural wavelet peak profiles of a file between two git revisions. Shows which structural boundaries (function/class definitions, imports, etc.) were added, removed, shifted, or changed in magnitude.

• file — absolute path to the file
• baseRef — base git ref (e.g. "HEAD~1", "main", a commit SHA)
• targetRef — target git ref (optional; omit to compare against the current working tree)
• minCoefficient — minimum wavelet coefficient threshold, 0–20 (default 0.3)
• limit — max peaks per revision, 1–500 (default 100)
• window — max line distance for matching peaks as "shifted", 1–50 (default 2). Higher values treat larger moves as shifts rather than remove+add.

Returns { beforeLineCount, afterLineCount, diff: { changes, summary } } where each change has kind (one of added, removed, shifted, magnitudeChanged, unchanged), before (the old peak, null for added), and after (the new peak, null for removed). The summary tallies counts for each kind.

Requires the file to be inside a git repository. A file that does not exist on one side (e.g. newly added so it is missing at baseRef, or deleted in the working tree when targetRef is omitted) is treated as empty — its peaks all show up as added or removed. An error is returned only when the file is missing on both sides.

update_cursor_position

Notify the server of the editor's current cursor position. The server precomputes wavelet context around the cursor so that subsequent get_cursor_context calls return instantly. Call this whenever the cursor moves significantly.

• file — absolute path to the file
• line — cursor line (0-indexed)
• column — cursor column (0-indexed)

Returns { acknowledged: true }.

get_cursor_context

Get the precomputed multi-resolution wavelet context around the editor's last known cursor position. Returns the cached result from update_cursor_position without recomputation. Returns an error if no cursor has been registered for the file.

• file — absolute path to the file

Return shape matches query_wavelet_context: center, clamped, bands (fine/medium/coarse), and waveletPeaks.

get_cursor_important_positions

Get structurally important positions near the current cursor, sorted by a combination of proximity and structural significance. Returns an error if no cursor has been registered for the file.

• file — absolute path to the file
• limit — max positions to return, 1–50 (default 10)

Returns an array of { position, coefficient, scale, label } objects, sorted closest-to-cursor first.

stream_start

Start a streaming project-wide query. Returns a stream_id immediately while results are computed in the background. Use stream_poll to fetch batches incrementally and stream_close to cancel.

• directory — absolute path to the project directory
• min_coefficient — minimum wavelet coefficient threshold, 0–20 (default 0.3)
• limit — maximum total results across all batches, 1–100 (default 20)
• batch_size — peaks per batch, 10–500 (default 50)

Returns { stream_id: "<uuid>" }.

stream_poll

Fetch the next batch of results from a streaming operation.

• stream_id — the ID returned by stream_start

Returns { peaks, more, complete } where more indicates further batches are queued and complete means the operation has finished. Returns an error for unknown/expired stream IDs. If the producer encountered an error, returns { error, complete: true }.

stream_close

Cancel a streaming operation and free its resources.

• stream_id — the ID returned by stream_start

Returns { acknowledged: true }. Idempotent for unknown IDs.

get_entropy_bands

Analyze the wavelet coefficient bands of a file for entropy using libwce bit-cost estimation. For each scale in the Ricker CWT, coefficients are quantized to integers, their Bit-Plane Counts are computed, and the encoding bit cost is estimated. Higher bit cost = more structural irregularity at that scale — a language-agnostic measure of local code complexity.

• file — absolute path to the file
• lossy_bits — LSBs to drop before BPC computation, 0–8 (default 0; higher is coarser)

Returns { bands, totalBitCost, meanBitCost } where each band carries its scale, bitCost, riceK, predictor, sparseFlag, and numGroups.

get_complexity_heatmap

Compute a multi-scale complexity heatmap for a file using a Haar DWT plus libwce. The per-line structural signal is decomposed, the encoding bit cost is estimated per detail band, and per-line irregularity scores are returned. Higher scores mark structurally dense/irregular regions — useful for review prioritization, context budgeting (keep irregular, summarize boilerplate), and navigation.

• file — absolute path to the file
• lossy_bits — LSBs to drop before BPC computation, 0–8 (default 0)

Returns { bands, totalEntropy, perLineIrregularity } where each band carries its level, span, bitCost, riceK, predictor, and sparseFlag.

Development

pnpm install         # Install dependencies + auto-build dist/
pnpm dev             # Run with tsx (live TypeScript)
pnpm test            # Watch mode
pnpm test:run        # Run tests once
pnpm test:coverage   # Run with coverage
pnpm typecheck       # Type check only

pnpm install runs the prepare script, which builds dist/ automatically. For a manual build, run pnpm build.

Supported languages

Python (.py, .pyi, .pyx), TypeScript (.ts, .tsx, .mts, .cts), JavaScript (.js, .jsx, .mjs, .cjs), Go, Rust, Java, Ruby (incl. Rakefile, Gemfile), PHP, Swift, Kotlin, Scala, Clojure (.clj, .cljs, .cljc, .edn).

Single-file tools (query_wavelet_context, get_important_positions with file, get_summary_at_scale, etc.) fall back to a minimal generic configuration for any extension not listed above.

Project-wide indexing (get_important_positions with directory, stream_start) is restricted to the listed extensions and known filenames (Rakefile, Gemfile) — unknown extensions are skipped to avoid burning budget on .md/.json/.csv/etc. that have little structural signal.

Project-wide indexing limits

When get_important_positions is called with directory, the indexer:

• honors a root-level .gitignore, including ! negation patterns (last-match-wins semantics, matching git's behavior); nested .gitignore files are not consulted;
• skips files larger than 2 MB and binary files (NUL byte sniff in first 4 KB);
• caps discovery at 5000 files (a truncated flag is set if exceeded);
• follows symlinks once via realpath, refusing any that escape the project root.