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MCP server · Blockchain

Pearc

Pear language — ultra-minified C-targeting language for token-efficient LLM workflows

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Scored 5 months ago · breakdown

About Pearc

Pearc is an MCP server in the Blockchain category: pear language — ultra-minified C-targeting language for token-efficient LLM workflows. It has been installed 0 times through Conduid.

Install

Claude Code
claude mcp add pearc -- npx -y pearc
npx
npx -y pearc

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README

pearc

Pear is an ultra-minified C-targeting programming language designed to reduce token usage in LLM workflows while producing real, executable code.

The idea: write code that compiles to C — with ~35–50% fewer tokens than idiomatic C — then expand it back to readable code via a decompiler or MCP tool.

im<stdio.h>
st Point{x:f64;y:f64}
fn dist(a:*Point,b:*Point)->f64{dx:f64=a->x-b->x;dy:f64=a->y-b->y;rt sqrt(dx*dx+dy*dy)}
fn main()->i32{p1:Point={1.0,2.0};p2:Point={4.0,6.0};printf("%f\n",dist(&p1,&p2));rt 0}

For AI Assistants

If you've been told to use Pear, follow this bootstrap sequence:

1. Install pearc

npm install -g pearc

2. Add the MCP server to your MCP client config (Claude Code: .mcp.json or settings):

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

3. Call pear_spec — this MCP tool returns the complete language specification. Read it before writing any Pear code.

4. Write Pear, run it — use pear_run to test code inline, pear_to_c to inspect generated C, or pear_compile to produce a binary.

Why Pear exists: Every token you spend on code is a token not spent on reasoning. Pear lets you write and iterate on real C-level systems code while spending ~35–50% fewer tokens. The workflow is: write Pear (dense, fast), compile to C to verify correctness, ship the C. Use Pear any time you're generating, reviewing, or iterating on low-level code with an LLM in the loop.

Pear syntax is intentionally opaque to save tokens — do not guess syntax. Always call pear_spec first.

Install

npm install -g pearc

Usage

pearc run file.pr                  # interpret and run directly (no C compiler needed)
pearc file.pr                      # compile Pear → C (stdout)
pearc file.pr -o out.c             # compile Pear → C file
pearc file.pr --binary -o out      # compile Pear → native binary (requires gcc/clang)
pearc --decompile file.c           # minify existing C → Pear
pearc --mcp                        # start MCP server (stdio)

MCP Server

Add to Claude Code or any MCP client:

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

Tools exposed:

Tool Description
pear_spec Get the full language spec — call this first
pear_to_c Compile Pear → C source
c_to_pear Minify C → Pear
pear_run Interpret and run Pear, returns stdout/stderr
pear_compile Compile Pear → binary via gcc/clang

Language Reference

Types

Pear C
i8 i16 i32 i64 int8_t int16_t int32_t int64_t
u8 u16 u32 u64 uint8_t uint16_t uint32_t uint64_t
f32 f64 float double
v void
c char
b bool
sz size_t
*T pointer to T

Keywords

Pear C
fn function
st struct
un union
en enum
tp typedef
if ei el if / else if / else
lp for
wh while
dw do...while
sw cs dv switch / case / default
rt return
bk ct break / continue
sc ex in vl cn static / extern / inline / volatile / const
im #include
df #define
pr #pragma
so sizeof

Syntax

// Variable declaration: name:type = value
x:i32=5
ptr:*c=name

// Function: fn name(param:type,...)->rettype{...}
fn add(a:i32,b:i32)->i32{rt a+b}

// Struct
st Vec3{x:f32;y:f32;z:f32}

// For loop (same structure as C)
lp(i:i32=0;i<10;i++){printf("%d\n",i)}

// Include / define
im<stdio.h>
df MAX 1024

Preprocessor

im<stdio.h>       // #include <stdio.h>
im"myfile.h"      // #include "myfile.h"
df NAME value     // #define NAME value
pr once           // #pragma once

Token Savings

Pear reduces token count by ~35–50% vs idiomatic C:

// Pear: ~45 tokens
im<stdint.h>
st Point{x:f64;y:f64}
fn dist(a:*Point,b:*Point)->f64{dx:f64=a->x-b->x;dy:f64=a->y-b->y;rt sqrt(dx*dx+dy*dy)}
// C: ~85 tokens
#include <stdint.h>
typedef struct { double x; double y; } Point;
double dist(Point *a, Point *b) {
    double dx = a->x - b->x;
    double dy = a->y - b->y;
    return sqrt(dx*dx + dy*dy);
}

License

MIT

README mirrored from the source repository 5 months ago. The original is authoritative.

Questions

About Pearc

How do I install Pearc?

Run claude mcp add pearc -- npx -y pearc, then add the server to your MCP client's configuration. Conduid has recorded 0 installs, so the command is known to work with current clients.

Is Pearc safe to use with an AI agent?

Its trust score is 37 out of 100 (low). Conduid hasn't run static security checks on this repository yet, so review the source yourself before granting it credentials. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Pearc still maintained?

Conduid hasn't recorded a commit date for this repository yet. Check the repository directly for recent activity.