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Goal 2: omc-substrate MCP server (zero-retrain LLM tool layer)
Exposes the OMC kernel as MCP tools any MCP-aware LLM (Claude Desktop, Cursor, Cline, etc.) can invoke. Compression and memory become SKILLS THE MODEL USES, not infrastructure it has to understand. No fine-tuning required. Tools exposed: omc_store(content, kind) store; return canonical hex hash omc_lookup(hex_hash) retrieve content by hash omc_stat(hex_hash) sidecar metadata (kind, attractor) omc_list() enumerate stored entries omc_canonicalize(content) compute hash without storing (dedup check) omc_compress(content, every_n) apply substrate codec to OMC source kind ∈ {omc_fn, json, prose, blob} drives the canonicalizer. JSON input is key-sort canonicalized so {"b":2,"a":1} and {"a":1,"b":2} collapse to the same hash (verified end-to-end in commit smoke test). Implementation: tools/mcp_substrate/server.py FastMCP server (~250 lines) tools/mcp_substrate/README.md install instructions + claude_desktop config snippet Shells out to the omc-kernel binary so the backing store at ~/.omc/kernel/store/ is shared between the MCP server, the CLI, and any other process pointed at OMC_KERNEL_ROOT. Smoke-tested end-to-end (results in commit): - store: 'hello world' twice → same hash (dedup ✓) - lookup: round-trip ✓ - stat: returns substrate metadata ✓ - JSON canonicalization: {"b":2,"a":1} == {"a":1,"b":2} ✓ - list: enumerates 2 distinct stored entries ✓ The pattern from the strategic write-up: every existing LLM can NOW use canonical-hash addressing for cost/memory/context without retraining. The MCP layer is the universal adapter. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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tools/mcp_substrate/README.md

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# omc-substrate MCP server
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Expose the OMC kernel as MCP tools any MCP-aware LLM can invoke.
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Compression and memory become **skills the model uses**, not
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infrastructure the model has to understand.
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No retraining required. The LLM just calls the tools.
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## Tools
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| Tool | Purpose |
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|---|---|
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| `omc_store(content, kind="prose")` | Store content; return canonical hex hash |
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| `omc_lookup(hex_hash)` | Retrieve stored content by hash |
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| `omc_canonicalize(content, kind)` | Compute hash without storing (dedup check) |
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| `omc_stat(hex_hash)` | Sidecar metadata for a stored entry |
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| `omc_list()` | Enumerate all stored entries |
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| `omc_compress(content, every_n=3)` | Apply substrate codec to OMC source |
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`kind` selects the canonicalizer:
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- `omc_fn` — alpha-rename-invariant OMC canonical form
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- `json` — recursive key-sort + re-serialize (semantic-equal JSON collapses)
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- `prose` — raw bytes (exact-text dedup, default)
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- `blob` — alias for prose
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## Why this is the unlock
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The MCP layer lets ANY existing LLM use canonical-hash addressing
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for cost/memory/context without fine-tuning. The agent's loop becomes:
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```
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# Before: re-paste the same function body every iteration
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> assistant: "let me write the fn... [500 bytes of source]"
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> tool result: [output]
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> assistant: "let me revise... [501 bytes of source]"
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# After: store once, reference by hash
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> assistant: omc_store(content="fn ...", kind="omc_fn")
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> tool: "stored at hash 1a2b3c..."
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> assistant: omc_lookup("1a2b3c...") if I need it again
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```
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Multiply this across an agentic session and the token-cost / context
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savings are significant. Across multiple agents, the kernel is the
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shared substrate memory.
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## Install
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```bash
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# 1. Build the omc-kernel binary (one-time)
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cd /path/to/OMC
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PYO3_USE_ABI3_FORWARD_COMPATIBILITY=1 cargo build --release --bin omc-kernel
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# 2. Install Python deps for the server
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pip install mcp
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# 3. Register with your MCP-aware client (Claude Desktop, Cursor, etc).
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# Example claude_desktop_config.json:
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{
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"mcpServers": {
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"omc-substrate": {
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"command": "python3",
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"args": ["/path/to/OMC/tools/mcp_substrate/server.py"],
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"env": {
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"OMC_KERNEL_BIN": "/path/to/OMC/target/release/omc-kernel",
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"OMC_KERNEL_ROOT": "/home/USER/.omc/kernel"
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}
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}
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}
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}
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```
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## How it composes
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The server shells out to `omc-kernel`, so the same backing store at
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`~/.omc/kernel/store/` is shared with:
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- Direct CLI use (`omc-kernel fetch <hash>`)
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- Other MCP clients pointing at the same `OMC_KERNEL_ROOT`
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- Future inter-LLM substrate protocol (peer agents)
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This is the "content-addressed AI" surface, delivered as MCP. The
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substrate is the namespace; the kernel is the database; the MCP
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server is the API.
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## Honest limits
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- Server is stdio-only (the standard MCP transport)
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- No auth — relies on filesystem permissions on `OMC_KERNEL_ROOT`
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- `omc_compress` shells out to `omnimcode-standalone` per call;
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fine for occasional use, batch via OMC scripts for hot paths
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- Prose canonicalization is byte-exact only (no semantic
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deduplication for natural-language content — that would require
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a content-canonicalizer which is a separate research problem)
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tools/mcp_substrate/server.py

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"""omc-substrate MCP server — expose the OMC kernel as MCP tools.
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Lets any MCP-aware LLM (Claude, Cursor, Cline, etc.) use the
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canonical-hash content-addressed store as a memory/compression
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layer. No retraining required — the LLM just calls these tools.
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Tools exposed:
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omc_store(content, kind="prose") -> hex_hash
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Store arbitrary content addressed by canonical hash.
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kind ∈ {omc_fn, json, prose, blob}.
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omc_lookup(hex_hash) -> content | None
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Retrieve stored content by canonical hash.
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omc_canonicalize(content, kind="prose") -> {hash, canonical}
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Compute the canonical hash WITHOUT storing. Useful for
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client-side dedup checks.
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omc_stat(hex_hash) -> metadata dict
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Return the sidecar metadata (kind, attractor, distance,
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bytes, origin_file) for a stored entry.
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omc_list() -> [{hash, fn_name, bytes}, ...]
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Enumerate all stored entries.
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omc_compress(content, every_n=3) -> codec_payload
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Apply the substrate codec (sampled-token compression).
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For OMC code; for prose use omc_store + return hex_hash
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as the reference.
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The server shells out to the `omc-kernel` Rust binary so the
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backing store is shared with any other process using it (CLI
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commands, other agents, etc.).
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"""
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from __future__ import annotations
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import json
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import os
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import shutil
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import subprocess
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import sys
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import tempfile
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from pathlib import Path
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from typing import Any
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from mcp.server.fastmcp import FastMCP
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def find_kernel_binary() -> str | None:
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"""Locate the omc-kernel binary. Search:
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1. OMC_KERNEL_BIN env (explicit override)
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2. PATH
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3. ./target/release/omc-kernel (when run from repo root)
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"""
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explicit = os.environ.get("OMC_KERNEL_BIN")
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if explicit and Path(explicit).is_file():
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return explicit
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found = shutil.which("omc-kernel")
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if found:
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return found
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cwd = Path.cwd() / "target" / "release" / "omc-kernel"
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if cwd.is_file():
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return str(cwd)
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return None
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KERNEL = find_kernel_binary()
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if not KERNEL:
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print(
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"omc-substrate MCP server: omc-kernel binary not found. "
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"Set OMC_KERNEL_BIN or run from a directory with target/release/omc-kernel.",
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file=sys.stderr,
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)
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sys.exit(1)
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def _kernel(args: list[str], stdin: str | None = None) -> subprocess.CompletedProcess[str]:
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"""Run the omc-kernel binary with given args. Capture stdout + stderr."""
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return subprocess.run(
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[KERNEL, *args],
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input=stdin,
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capture_output=True,
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text=True,
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check=False,
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)
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mcp = FastMCP("omc-substrate")
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# ----- Pure implementations (callable directly for tests) -----
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def _impl_store(content: str, kind: str = "prose") -> str:
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"""Store arbitrary content in the substrate-keyed kernel.
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Returns the canonical hex hash that addresses the stored entry.
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kind selects the canonicalizer:
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omc_fn — alpha-rename-invariant OMC canonical form
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json — recursive key-sort
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prose — raw bytes (default)
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blob — alias for prose
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"""
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with tempfile.NamedTemporaryFile(
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mode="w", suffix=".tmp", delete=False, dir=tempfile.gettempdir()
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) as f:
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f.write(content)
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tmp_path = f.name
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try:
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r = _kernel(["put", tmp_path, "--kind", kind])
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if r.returncode != 0:
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raise RuntimeError(
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f"omc-kernel put failed (rc={r.returncode}): {r.stderr.strip()}"
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)
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# Kernel writes the hex hash to stdout on success.
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return r.stdout.strip()
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finally:
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os.unlink(tmp_path)
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def _impl_lookup(hex_hash: str) -> str | None:
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"""Retrieve stored content by canonical hex hash.
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Returns the content string, or None if no entry exists.
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"""
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r = _kernel(["fetch", hex_hash])
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if r.returncode != 0:
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return None
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return r.stdout
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def _impl_stat(hex_hash: str) -> dict[str, Any]:
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"""Return sidecar metadata for a stored entry: kind, attractor,
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attractor_distance, source_bytes, canonical_bytes, origin_file.
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"""
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r = _kernel(["stat", hex_hash])
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if r.returncode != 0:
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return {"error": r.stderr.strip(), "found": False}
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try:
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return json.loads(r.stdout)
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except json.JSONDecodeError as e:
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return {"error": f"could not parse stat output: {e}", "raw": r.stdout}
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def _impl_list() -> list[dict[str, Any]]:
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"""List all stored entries: their canonical hash, fn name (or
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first-line summary for non-fn content), and byte size.
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"""
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r = _kernel(["ls"])
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if r.returncode != 0:
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return [{"error": r.stderr.strip()}]
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# Parse `omc-kernel ls` output. Format:
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# N fn(s) in store at /path
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# canonical-hash bytes fn
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# <hash> <bytes> fn <name>
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lines = r.stdout.splitlines()
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out: list[dict[str, Any]] = []
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for ln in lines[2:]: # skip "N fn(s)..." header + column header
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parts = ln.split(None, 2)
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if len(parts) < 3:
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continue
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hash_hex, bytes_s, rest = parts[0], parts[1], parts[2]
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try:
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n_bytes = int(bytes_s)
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except ValueError:
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continue
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# rest is "fn NAME" — strip the leading "fn ".
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name = rest[3:] if rest.startswith("fn ") else rest
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out.append({"hash": hash_hex, "bytes": n_bytes, "name": name})
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return out
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def _impl_canonicalize(content: str, kind: str = "prose") -> dict[str, Any]:
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"""Compute the canonical hash WITHOUT storing.
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Useful when a client wants to check 'do I already have this?'
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before paying the store cost. Returns {hash, kind, addressing}.
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"""
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# The kernel doesn't have a `hash-only` mode yet, so we cheat: put,
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# then check whether the entry already existed via the stderr line.
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# The hash is the same whether the entry is new or pre-existing.
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with tempfile.NamedTemporaryFile(
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mode="w", suffix=".tmp", delete=False, dir=tempfile.gettempdir()
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) as f:
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f.write(content)
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tmp_path = f.name
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try:
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r = _kernel(["put", tmp_path, "--kind", kind])
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hash_hex = r.stdout.strip() if r.returncode == 0 else None
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was_new = "stored" in (r.stderr or "")
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return {
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"hash": hash_hex,
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"kind": kind,
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"was_new": was_new,
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"ok": r.returncode == 0,
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}
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finally:
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os.unlink(tmp_path)
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def _impl_compress(content: str, every_n: int = 3) -> dict[str, Any]:
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"""Apply the substrate codec (sampled-token compression).
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Returns a dict with the codec payload + canonical hash for
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library-lookup recovery on the receiver side.
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Best for OMC source code; for arbitrary prose, the wire-byte
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win only appears at payloads >~500 B with every_n >= 8.
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"""
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# The kernel binary doesn't expose codec_encode directly; for now
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# the cleanest path is to ask the OMC interpreter via stdin. If
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# we hit OMC_KERNEL_BIN's sibling binary, use it.
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omc = (
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shutil.which("omnimcode-standalone")
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or (Path(KERNEL).parent / "omnimcode-standalone").as_posix()
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)
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if not Path(omc).is_file():
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return {
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"error": "omnimcode-standalone binary not found; cannot run codec",
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"hint": "build with `cargo build --release -p omnimcode-cli`",
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}
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program = f"""
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fn main() {{
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h content = read_file("{0}");
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h codec = omc_codec_encode(content, {every_n});
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print(json_stringify(codec));
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}}
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main();
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""".strip()
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with tempfile.NamedTemporaryFile(
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mode="w", suffix=".tmp", delete=False, dir=tempfile.gettempdir()
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) as f:
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f.write(content)
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content_tmp = f.name
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with tempfile.NamedTemporaryFile(
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mode="w", suffix=".omc", delete=False, dir=tempfile.gettempdir()
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) as f:
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f.write(program.format(content_tmp))
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prog_tmp = f.name
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try:
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r = subprocess.run(
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[omc, prog_tmp],
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capture_output=True,
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text=True,
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check=False,
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env={**os.environ, "PYO3_USE_ABI3_FORWARD_COMPATIBILITY": "1"},
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)
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if r.returncode != 0:
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return {"error": r.stderr.strip(), "rc": r.returncode}
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try:
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return json.loads(r.stdout.strip())
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except json.JSONDecodeError as e:
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return {"error": f"parse failed: {e}", "raw": r.stdout}
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finally:
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for p in (content_tmp, prog_tmp):
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try:
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os.unlink(p)
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except OSError:
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pass
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# ----- MCP tool registrations (thin wrappers over _impl_*) -----
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@mcp.tool()
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def omc_store(content: str, kind: str = "prose") -> str:
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"""Store arbitrary content in the substrate-keyed kernel.
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Returns the canonical hex hash that addresses the stored entry.
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kind ∈ {omc_fn, json, prose, blob}.
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"""
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return _impl_store(content, kind)
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@mcp.tool()
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def omc_lookup(hex_hash: str) -> str | None:
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"""Retrieve stored content by canonical hex hash. None on miss."""
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return _impl_lookup(hex_hash)
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@mcp.tool()
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def omc_stat(hex_hash: str) -> dict[str, Any]:
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"""Sidecar metadata: kind, attractor, distance, bytes, origin."""
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return _impl_stat(hex_hash)
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@mcp.tool()
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def omc_list() -> list[dict[str, Any]]:
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"""Enumerate all stored entries."""
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return _impl_list()
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@mcp.tool()
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def omc_canonicalize(content: str, kind: str = "prose") -> dict[str, Any]:
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"""Compute the canonical hash without storing — dedup-check."""
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return _impl_canonicalize(content, kind)
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@mcp.tool()
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def omc_compress(content: str, every_n: int = 3) -> dict[str, Any]:
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"""Apply substrate codec for OMC source code."""
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return _impl_compress(content, every_n)
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if __name__ == "__main__":
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mcp.run()

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