CostAffective-MCP

@Yash Gajjar

Visit Server

4 hours ago

# code-search

# developer-tools

# knowledge-base

# repository-management

# mcp

# mcp-server

Intelligent repository context for AI coding assistants. Provides code search, symbol lookup, call graphs, and reference tracking via MCP. Uniquely designed to minimize prompt-cache costs in long sessions stash/recall/remember tools keep large content out of context until needed, and a token-budgeted repository summary avoids unbounded prompt bloat. Works with any MCP client (Claude, Codex, Cursor, opencode, etc..). Go, CGO, tree-sitter-backed.

Overview Tools Comments

Overview

costaffective-mcp

Coding agents that explore less, remember more, and carry less context.

MCP:

github.com/okyashgajjar/costaffective-mcp

CostAffective is a local MCP server that makes AI coding agents behave like experienced engineers. Instead of re-reading whole files every turn, dumping build logs into context, and re-discovering symbols they already found, agents get fast, token-budgeted access to your repository — so they stop carrying everything around forever.

Why

In long sessions the dominant cost is not the model's output — it's the prompt cache re-reading and re-writing everything resident in the context window every turn. A real measured example: a single API call billed at $2.95, of which $2.84 was a 5-minute cache write of ~455k tokens of resident context. The answer was under 4,000 tokens.

CostAffective fixes this by keeping tokens out of the window in the first place.

Tools (11 MCP tools)

Retrieval

search_code — semantic repository search by natural language question
find_symbol — locate where a symbol is defined
read_symbol — return a symbol's full implementation body by name
find_references — every usage of a symbol, precomputed
find_callers — which functions call a given function

Context control

remember — persist a durable fact once instead of repeating it inline
stash_context — park a large blob (file, log, output) out of context behind a tiny handle
recall — pull back only the slice matching a query, within a token budget

Maintenance

get_repository_summary — token-budgeted repo overview, drillable by module
index_repository — manual re-index trigger

Session awareness

costaffective-session skill — 275-token guidance auto-delivered via MCP instructions field, teaching agents to stash, remember, and retrieve instead of pasting inline

Architecture

AI Client (MCP Host) → stdio transport → costaffective serve
  ├── Tree-sitter parser → Symbol / Reference / Call Graph indexes
  ├── Per-repo stash (large blobs out of context)
  ├── Per-repo durable facts (remember/recall)
  └── Token-budgeted compression on every tool output

All per-repo state lives under .mycli-fts/ in the repo root. Index is local SQLite. No cloud, no API keys.

Benchmarks

Small repo: tokens consumed dropped 81.7% (299K → 55K), 2.2x faster, 70% fewer tool calls. Large repo (Continue OSS): tokens down 45.9% (8.7M → 4.7M), API calls down 33.6%.

Install

curl -fsSL https://raw.githubusercontent.com/okyashgajjar/costaffective-mcp/main/install.sh | bash

Or manual: CGO_ENABLED=1 go build -o costaffective ./cmd/costaffective/

Server config for any MCP client:

{
  "mcpServers": {
    "costaffective": {
      "command": "costaffective",
      "args": ["serve"]
    }
  }
}

Supports Claude Code, Cursor, OpenCode, Cline, Codex CLI, Antigravity, and any stdio MCP client.

Requirements

Go 1.25+, C compiler (CGO required for go-sqlite3 and tree-sitter). Linux amd64/arm64, macOS amd64/arm64, Windows amd64.

Build with ShipAny.