Gcf Typescript

gcf-typescript

TypeScript implementation of GCF — the most token-efficient wire format for LLMs. A drop-in alternative to JSON and TOON for any structured data.

100% comprehension on every frontier model tested. 29% fewer tokens than TOON, 56% fewer than JSON across 16 datasets. 91.2% on structurally complex code graphs (vs TOON 68.8%, JSON 54.1%). 2,400+ LLM evaluations. Zero training.

Docs: gcformat.com · Playground · GCF vs TOON

Install

npm install @blackwell-systems/gcf

Zero dependencies. TypeScript-first. Includes CLI. Don't want to change code? Use the MCP proxy for zero-code adoption.

CLI

npx @blackwell-systems/gcf encode < payload.json    # JSON to GCF
npx @blackwell-systems/gcf decode < payload.gcf     # GCF to JSON
npx @blackwell-systems/gcf stats  < payload.json    # token comparison

Payload: 50 symbols, 20 edges

  JSON  ██████████████████████████████  4,200 tokens
  GCF   ████████░░░░░░░░░░░░░░░░░░░░░░  1,150 tokens

  Savings: 73% fewer tokens with GCF

Or install globally: npm install -g @blackwell-systems/gcf then use gcf directly.

Library

Quick Start

import { encodeGeneric } from '@blackwell-systems/gcf';

const output = encodeGeneric({
  employees: [
    { id: 1, name: 'Alice', department: 'Engineering', salary: 95000 },
    { id: 2, name: 'Bob', department: 'Sales', salary: 72000 },
  ],
});

Output:

## employees [2]{id,name,department,salary}
1|Alice|Engineering|95000
2|Bob|Sales|72000

Decode

import { decode } from '@blackwell-systems/gcf';

const p = decode(input);
console.log(p.tool, p.symbols.length, 'symbols', p.edges.length, 'edges');

Session Deduplication

Track transmitted symbols across multiple tool responses. Previously-sent symbols become bare references instead of full declarations:

import { Session, encodeWithSession } from '@blackwell-systems/gcf';

const sess = new Session();

const out1 = encodeWithSession(payload1, sess); // full declarations
const out2 = encodeWithSession(payload2, sess); // reused symbols as "@N  # previously transmitted"

By the 5th call in a session: 92.7% token savings vs JSON.

Streaming Encode

Write GCF output incrementally as symbols and edges arrive. Zero buffering, O(1) memory per row. Ideal for MCP servers that walk large graphs or paginate results:

import { StreamEncoder } from '@blackwell-systems/gcf';

const enc = new StreamEncoder(writer, 'context_for_task', { tokenBudget: 5000 });

// Symbols emit immediately as they're discovered.
enc.writeSymbol({ qualifiedName: 'pkg.Auth', kind: 'function', score: 0.95, provenance: 'lsp', distance: 0 });
enc.writeSymbol({ qualifiedName: 'pkg.Server', kind: 'function', score: 0.60, provenance: 'lsp', distance: 1 });

// Edges emit immediately too.
enc.writeEdge({ source: 'pkg.Server', target: 'pkg.Auth', edgeType: 'calls' });

// Close emits the ## _summary trailer with final counts.
enc.close();

Output:

GCF tool=context_for_task budget=5000
## targets
@0 fn pkg.Auth 0.95 lsp
## related
@1 fn pkg.Server 0.60 lsp
## edges [?]
@0<@1 calls
## _summary symbols=2 edges=1 sections=targets:1,related:1,edges:1

The writer is any object with a write(s: string) method (Node.js streams, web WritableStreams, or a simple callback). Standard decode() handles streaming output with no changes.

Delta Encoding

When the consumer already has a prior context pack, send only what changed:

import { encodeDelta, type DeltaPayload } from '@blackwell-systems/gcf';

const delta: DeltaPayload = {
  tool: 'context_for_task',
  baseRoot: 'aaa111',
  newRoot: 'bbb222',
  removed: [{ qualifiedName: 'pkg.OldFunc', kind: 'function', score: 0, provenance: '', distance: 0 }],
  added: [{ qualifiedName: 'pkg.NewFunc', kind: 'function', score: 0.85, provenance: 'rwr', distance: 0 }],
  removedEdges: [],
  addedEdges: [],
  deltaTokens: 30,
  fullTokens: 200,
};

const output = encodeDelta(delta);

81.2% savings on re-queries where the pack changed slightly.

Generic Encoding

Encode any JS value (not just graph payloads) into GCF tabular format:

import { encodeGeneric } from '@blackwell-systems/gcf';

const output = encodeGeneric({
  employees: [
    { id: 1, name: 'Alice', department: 'Engineering', salary: 95000 },
    { id: 2, name: 'Bob', department: 'Sales', salary: 72000 },
  ],
});

Output:

## employees [2]{id,name,department,salary}
1|Alice|Engineering|95000
2|Bob|Sales|72000

Works on objects, arrays, and primitives. Arrays of uniform objects get tabular rows. Nested objects use ## key section headers.

API

| Function | Description | |----------|-------------| | encode(p: Payload): string | Encode a graph payload to GCF text | | encodeGeneric(data: unknown): string | Encode any value to GCF tabular format | | decode(input: string): Payload | Parse GCF text back to a Payload | | encodeWithSession(p: Payload, s: Session): string | Encode with session deduplication | | new StreamEncoder(w, tool, opts) | Create a streaming encoder (zero-buffering) | | encodeDelta(d: DeltaPayload): string | Encode a delta (added/removed only) | | new Session() | Create a new session tracker |

Types

| Type | Purpose | |------|---------| | Payload | Full GCF payload: tool, budget, symbols, edges, pack root | | Symbol | Graph node: qualified name, kind, score, provenance, distance | | Edge | Directed relationship: source, target, edge type | | DeltaPayload | Diff between two packs: added/removed symbols and edges | | Session | Tracker for multi-call deduplication | | KIND_ABBREV / KIND_EXPAND | Bidirectional kind abbreviation maps |

Benchmarks

2,400+ LLM evaluations across 10 models, 3 providers, and 51 independent test runs.

| | GCF | TOON | JSON | |---|---|---|---| | Comprehension (23 runs, 10 models) | 91.2% | 68.8% | 54.1% | | Generation (28 runs, 9 models) | 5/5 | 1.0/5 | 5.0/5 | | Input tokens (500 symbols) | 11,090 | 16,378 | 53,341 | | Output tokens (100 symbols) | 5,976 | 8,937 | 16,121 |

GCF wins 15/16 datasets on the expanded token efficiency benchmark. Full results: gcformat.com/guide/benchmarks

Implementations

| Language | Package | Repository | |----------|---------|-----------| | Go | go get github.com/blackwell-systems/gcf-go | gcf-go | | TypeScript | npm install @blackwell-systems/gcf | gcf-typescript | | Python | pip install gcf-python | gcf-python | | Rust | cargo add gcf | gcf-rust | | Swift | Swift Package Manager | gcf-swift | | Kotlin | JitPack | gcf-kotlin | | MCP Proxy | pip install gcf-proxy | gcf-proxy (bidirectional, session dedup, HTTP frontend) | | Claude Code Plugin | /plugin install | gcf-claude-plugin (one-command install, session stats hook) | | Codex Plugin | codex plugin add | gcf-codex-plugin (one-command install, session stats hook) | | VS Code | ext install blackwell-systems.gcf-vscode | gcf-vscode (syntax highlighting) | | n8n | npm install n8n-nodes-gcf | gcf-n8n-nodes (workflow encode/decode) | | Tree-sitter | npm install tree-sitter-gcf | tree-sitter-gcf |

Zero runtime dependencies. Permanently. All six implementations depend only on their language's standard library. No transitive dependencies. No supply chain risk. This is a permanent commitment: GCF will never take on external runtime dependencies. MIT licensed. All implementations support both generic profile (encodeGeneric) and graph profile (encode). CLI included in all 6 languages.

Specification: SPEC v3.2 Stable with 174 conformance fixtures, 43,000,000,000+ lossless round-trips verified across 5 formats and 6 languages. All implementations at v2.2.1+ (Go v1.3.1). Cross-language 6x6 matrix verified.

License

MIT - Dayna Blackwell

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: blackwell-systems
• Source: blackwell-systems/gcf-typescript
• License: MIT
• Homepage: https://www.gcformat.com

Install and usage instructions live in the source repository linked above.