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PopNx MCPMCP servers for people who use AI · explained in plain words

Smart Context MCP

by Arrayoversion 1.21.0i★ –iRuns on your computer
Registry nameio.github.Arrayo/smart-context-mcp

Install

Overview

Description from the maker (original English)

Reduces AI agent token usage by 90% via context compression and task checkpoint persistence.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Docs, sheets & office work

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "smart-context": {
      "command": "npx",
      "args": [
        "-y",
        "smart-context-mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add smart-context -- npx -y smart-context-mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "smart-context": {
      "command": "npx",
      "args": [
        "-y",
        "smart-context-mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "smart-context": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "smart-context-mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account Arrayo, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Docs, sheets & office worki

  • More stars than 0% of the other 2167 servers in this category
  • Published to the registry more recently than 39% of the other 2167 servers in this category
  • Basic checks equal to or better than 100% of the other 2167 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Smart Context MCP safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.21.0) reached the registry 2 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Agent-Native Calendar, Excel MCP Server, MCP Server for Excel

Alternatives

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Runs on your computer★ 4,276MITUpdated 5 days ago
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Excel automation for AI - Sheets, Power Query, DAX, VBA, Tables, Ranges and more. Windows only.

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

smart-context-mcp

MCP server that reduces AI agent token usage by up to 90% through intelligent context compression (measured on this project).

What it is

An MCP (Model Context Protocol) server that provides specialized tools for reading, searching, and managing code context efficiently. Instead of loading full files or returning massive search results, it compresses information while preserving what matters for the task.

Real metrics from production use:

  • ~7M tokens → ~800K tokens (approximately 89% reduction)
  • 1,500+ operations tracked across development
  • Compression ratios: 3x to 46x depending on tool
  • Context overhead is tracked separately so reports can show gross and net savings

Workflow-level savings:

  • Debugging: ~85-90% token reduction
  • Code Review: ~85-90% token reduction
  • Refactoring: ~85-90% token reduction
  • Testing: ~85-90% token reduction
  • Architecture: ~85-90% token reduction

Real adoption in non-trivial tasks:

  • Approximately 70-75% of complex tasks use devctx tools
  • Most used: smart_read (850+ uses), smart_search (280+ uses), smart_shell (220+ uses)
  • Primary reasons for non-usage: task too simple, no index built, native tools preferred

See Workflow Metrics and Adoption Metrics for details.

Latest Release: 1.21.0

Minor release built around a semantic engine. MCP grows from 20 → 22 tools (smart_code + smart_output). SQLite schema bumps 8 → 9 (new outputs table; auto-migrates on first run). Zero new runtime dependencies — the TypeScript LanguageService comes from the typescript package you already have, and degrades to a fallback provider when it isn't there.

  • `smart_code` (new tool). Semantic code navigation for JS/TS via the TypeScript LanguageService, resolving by symbol name (plus optional filePath) instead of forcing you to know a line and column. Actions: definition, references, implementations, diagnostics, impact, rename. Returns compact locations (file + 1-based start/end), never full file bodies. includeTests=false drops test paths; maxResults caps the payload.
  • Impact analysis. smart_code(action='impact') splits direct hits (semantic: definitions, references, implementations) from transitive files (import graph, maxHops default 2) and related tests, plus coverage flags. risk.level is labelled basis: 'heuristic' and says so in its own note — it is a ranking aid, not semantic certainty.
  • Scope-aware rename, dry run by default. smart_code(action='rename') uses findRenameLocations and `dryRun: true` is the default: the first call returns the planned per-file diff hunks (before/after per line) and writes nothing. Error conflicts (invalid or reserved newName, same name, unresolved target, path escape, missing file, blast radius over maxFiles) always block the write. name-collision is a heuristic warning that only blocks with strict: true, because the check doesn't verify scope overlap. After a real write, diagnosticsAfter reports remaining TypeScript errors in the touched files. smart_edit remains the tool for non-semantic textual replacements.
  • `smart_output` (new tool). Persistent output/artifact store (shell, test, build, lint, diff) so a stack trace from twenty turns ago is recoverable without rerunning the command. Actions: save, search, excerpt, summary, list, stats, prune. Content is scrubbed for likely secrets before persistence and truncated head+tail above DEVCTX_OUTPUT_MAX_BYTES (256KB) so the failing tail always survives. Retention via DEVCTX_OUTPUT_RETENTION_DAYS (14) and DEVCTX_OUTPUT_MAX_PER_KIND (50). Identical output for the same kind+command is deduped into repeat_count. Automatic capture from smart_shell/smart_test is opt-in via DEVCTX_OUTPUT_STORE=true (then smart_shell returns an outputRef); explicit save/search always work. Degrades with degraded: true instead of throwing when SQLite is unavailable or locked.
  • Opt-in semantic expansion in `smart_context`. include: ['semantic'] expands context through real definitions, references and implementations rather than text similarity, and every item gains a whyIncluded explanation. Off by default until the precision@5 benchmark justifies otherwise.
  • Richer ADR/spec awareness and graph paths carried over from the same roadmap: ADR sections are indexed as kind='adr' / 'adr-section', and smart_context can return graph paths between two files or symbols.
  • Shared `tokenBudget` across tools. smart_read, smart_read_batch, smart_context, smart_turn (start + end) and smart_resume now accept tokenBudget: number | { id?, maxTokens, shared? }. When shared:true (or id set), the budget is reused across calls inside the same task — so a multi-step agent flow can stay under a hard token ceiling without per-call bookkeeping. Responses include taskBudget, remainingBudget, and budgetDetails (scope, actions, degraded mode) when the budget actually changed the output.
  • `smart_search` search modes. New mode: 'needle' | 'balanced' | 'semantic' (default balanced). needle = literal exact only (no regex / no term expansion) — kills noise on debug queries. balanced = exact + regex + term expansion. semantic = exact-first plus the local semantic block only when exact signal is weak. The previous semantic: true flag remains as a legacy alias for mode: 'semantic'. Default maxFiles tightened 15 → 5. New maxTokens caps the whole response and compacts intelligently (matches first, then diagnostics, then semantic block). Per-file ranking is now inspectable via matchedBy, boostSource, scoreBreakdown, whyRanked. Response also returns hasMore / totalFiles / nextSuggestedMaxFiles and actionable suggestions when the query is too broad or empty.
  • `smart_read` persistent cache + budget-aware `full` degradation. New SQLite read_cache table keyed by (filePath, mode, selector, content_hash). Second read of an unchanged file is virtually free. Mode full is now an explicit last resort: if a tokenBudget/maxTokens is set, it degrades to lighter modes first (outline → signatures → truncated) and reports the real mode used in fullMode + budgetDetails. New clearReadCachePersistent + GC integration in runStorageMaintenance.
  • `smart_turn` simple-task skip heuristic. When the prompt is short (≤ 40 chars after normalization), classified as a simple task, and no session/task is pinned, smart_turn(start) now returns skipSmartTurn: true with recommendedPath.mode='simple_task_skip' instead of paying the full orchestration cost. Saves continuity-resolution overhead on trivial prompts. minimal verbosity additionally compacts summary/refreshedContext to the fields agents actually consume.
  • `global_memory` noise hints. Per-project, scrubbed noise telemetry persisted to ~/.devctx/global.db (noise_hints table). New actions noise_stats and noise_reset (full or via query). Lets smart_search learn which queries the agent already discovered to be noisy in a given repo and adjust ranking, without ever leaking content.
  • KPI baseline infrastructure. New scripts evals/kpi-baseline.js + evals/kpi-utils.js aggregate harness.js and realworld-eval.js runs into a single JSON snapshot with top-5 precision, recall, reread task/call rate, and per-task-size buckets (short / long). Persists kpi-baseline-latest.json for regression detection across releases. New test suite tests/eval-kpis.test.js.
Highlights from 1.20.0 (still current)

Same tool count as 1.19.0, but several tools gained hard token-budget control, search-mode discipline and second-read cache reuse.

  • Shared `tokenBudget` across tools. smart_read, smart_read_batch, smart_context, smart_turn and smart_resume accept tokenBudget: number | { id?, maxTokens, shared? }, reusable across calls inside one task so a multi-step flow stays under a hard ceiling.
  • `smart_search` modes. mode: 'needle' | 'balanced' | 'semantic' (default balanced), maxTokens capping the whole response, and inspectable ranking via matchedBy / scoreBreakdown / whyRanked.
  • `smart_read` persistent cache. SQLite read_cache keyed by (filePath, mode, selector, content_hash); a second read of an unchanged file is virtually free. Mode full degrades to lighter modes under a budget and reports the real mode used.
  • `smart_turn` simple-task skip on short trivial prompts, and `global_memory` noise hints that let smart_search learn which queries proved noisy per repo.
  • KPI baseline infrastructure (evals/kpi-baseline.js) snapshotting precision@5, recall, reread rate and latency for regression detection.
Highlights from 1.19.0

Five-step quality jump executed as sequential commits with full dogfooding. MCP grew from 18 → 20 tools, +68 tests, zero new dependencies.

  • `smart_playbook` (new tool). Declarative composite workflows that run multiple smart_* tools in a single MCP call. Five built-in playbooks ship with the package: preflight-merge (review + affected tests + checkpoint), debug-flake (last failure + curated debug context + affected), refactor-safe (curated context + affected + checkpoint), doc-sync (ADR search + docs context), ramp-up (status + doctor + ADR overview). Project-level overrides via .devctx/playbooks/*.{yaml,json} with {{args.X}} interpolation, when / label / stopOnFail / dryRun. Tool allowlist restricted to smart_*. Zero deps: built-in minimal YAML parser.
  • Reactive FS watcher for the index. fs.watch (native, recursive, debounced 600ms + batch flush every 2s) keeps the symbol index hot between calls. Filters .git, node_modules, .devctx, dist, build, lockfiles, .min.*, .map, .snap, and non-indexable extensions. Stats surface in smart_status (enabled, flushes, eventsObserved, filesReindexed, filesRemoved, errors, lastFlushAt, pending). Opt-out via DEVCTX_WATCH_INDEX=false. Wired to MCP shutdown for clean close + final flush.
  • Richer Python / Go parsers + pluggable parser registry. Python now captures decorators (decorators: ["dataclass", ...]), async def (kinds async-function / async-method), TypeAlias and TypeVar / NewType / ParamSpec / TypeVarTuple as kind="type", and respects class indent for accurate scope. Go now captures methods with receiver type as parent, interfaces as kind="interface", top-level const / var. src/parsers/registry.js exposes registerParser / getParser so future tree-sitter parsers can plug in without touching index.js. INDEX_VERSION bumped 6 → 7 (auto-reindex).
  • Local semantic re-rank on `smart_search`. Opt-in semantic: true (with semanticLimit) returns a semantic: { embedder, symbols[], files[] } block ranked by hashing/TF-IDF embeddings (256-dim, FNV-1a buckets, L2-normalized, cosine similarity, <5ms). Default behavior unchanged. Pluggable embedder interface (id, dimensions, embed, similarity) ready to swap in ONNX/transformers without touching callers.
  • `global_memory` (new tool, opt-in). Cross-project memory persisted to ~/.devctx/global.db (override via DEVCTX_GLOBAL_DB, gated by DEVCTX_GLOBAL_MEMORY=true). St

Only the beginning is shown; read the rest in the repo

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