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Lexicon

NPM · @ASHLR/LEXICON · SCANNED SEP 28

Fixes the names and jargon speech-to-text gets wrong before your agent acts on a dictated prompt.

Available components

69 Trust /100
Trust breakdown (7 categories)

How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score → Why this is hard to score →

Supply Chain Security98
  • No malware found by supply-chain analysis.Pass
  • No known CVEs affecting this package version or its production dependencies.Pass
  • No install/post-install scripts declared.Pass
  • 33 of 96 dependencies flagged as unhealthy. View diagnostics → Partial
Provenance & Transparency48
  • Source repository is publicly reachable at the declared URL. View diagnostics → Pass
  • Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
  • Clear OSI-approved license (MIT).Pass
  • Actively maintained (last published 6 days ago).Pass
  • Publishes a security disclosure policy (SECURITY.md).Pass
Schema Quality & AI Usability79
  • 100% of prompts and resources have a non-trivial description (not blank, and not just the item's name).Pass
  • AI-judged instruction clarity (excellent).Pass
  • Context-footprint check failed: tool/resource definitions use about 4744 tokens (~225/item across 21 items; 19 tools + 2 resources), over budget; trim descriptions and params. See how to fix → Fail
  • Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management0
  • Stability not yet verified: not enough scan history yet (needs a 30-day window).Unverified
Tool Coverage96
  • 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
  • 88% of tool parameters carry a description.Partial
Tool Safety75
  • No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
  • 0 of 1 tool(s) whose name or description implies an irreversible operation declare an MCP destructiveHint annotation; "remove_term" implies "remove" and declares no destructiveHint at all, which the MCP spec reads as destructive by default. See how to fix → Fail
  • An AI judge read all 21 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
  • Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass

Unverified: 1 category

A category scored 0 because we could not verify it: a data source with nothing on this package, evidence we could not reach, or a check we could not run. We only credit what we can confirm.

Install

How do I install the Lexicon MCP server?

Lexicon runs locally as an npm package, launched with npx -y @ashlr/lexicon. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

npm · @ashlr/lexicon

# add to Claude Code
claude mcp add ashlrai-lexicon -- npx -y @ashlr/lexicon
// .cursor/mcp.json
{
  "mcpServers": {
    "ashlrai-lexicon": {
      "command": "npx",
      "args": [
        "-y",
        "@ashlr/lexicon"
      ]
    }
  }
}
// .vscode/mcp.json
{
  "servers": {
    "ashlrai-lexicon": {
      "command": "npx",
      "args": [
        "-y",
        "@ashlr/lexicon"
      ]
    }
  }
}
# add to Codex CLI
codex mcp add ashlrai-lexicon -- npx -y @ashlr/lexicon
// opencode.json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "ashlrai-lexicon": {
      "type": "local",
      "command": [
        "npx",
        "-y",
        "@ashlr/lexicon"
      ],
      "enabled": true
    }
  }
}
# add to OpenClaw
openclaw mcp add ashlrai-lexicon --command npx --arg -y --arg @ashlr/lexicon
# ~/.hermes/config.yaml
mcp_servers:
  ashlrai-lexicon:
    command: "npx"
    args: ["-y", "@ashlr/lexicon"]
// ~/.netclaw/config/netclaw.json
{
  "McpServers": {
    "ashlrai-lexicon": {
      "Transport": "stdio",
      "Command": "npx",
      "Arguments": [
        "-y",
        "@ashlr/lexicon"
      ]
    }
  }
}
# add to Vellum
assistant mcp add ashlrai-lexicon -t stdio -c npx -a -y @ashlr/lexicon
// mcp.json
{
  "mcpServers": {
    "ashlrai-lexicon": {
      "command": "npx",
      "args": [
        "-y",
        "@ashlr/lexicon"
      ]
    }
  }
}
Changelog

Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.

  • 28 Sept 26 69

    First indexed and scored.

Diagnostics

Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.

Captured 28 Sept 2026 · Analysed npm/@ashlr/lexicon@0.5.4

Provenance No attestation

The registry publishes no build provenance for this version, so there is nothing to verify.

Result No attestation
Ecosystem npm

Background: How many MCP packages publish verified provenance →

Dependencies 96 packages
Packages resolved 96
Stale 33
Tree resolution Complete

Background: SBOMs and build attestations, explained →

MCP tools · 19 exposed · ~4,051 tokens

The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →

Tool Tokens
add_pack ~132

Install one starter pack from list_packs into the global lexicon (or the project .lexicon.yaml with scope: project). Adds the pack's terms with source "pack"; a term the user already has keeps its own spelling and aliases and only gains the pack's. Idempotent. A pack is sixty-odd terms, so name the pack and ask before calling this. Remove one later with `lexicon pack remove <name>`.

NameTypeReqDescription
namestringyesPack name from list_packs, e.g. developer.
scopestring–'global' (default) or 'project'.

No output schema declared.

No examples provided.

add_term ~378

Teach the lexicon a name, so dictation is corrected to it from now on. WHEN TO CALL: when the user names something they want spelled a particular way, or during setup for each extra name they give you. For the one specific case of the user correcting a spelling that came out wrong, prefer learn_correction: it finds the right term for you. Do not add a name the user did not ask you to remember. WHAT IT CHANGES: writes one term to the user's lexicon file (global by default, or the repo's .lexicon.yaml with scope: 'project'). It merges rather than clobbers: an existing term with the same canonical keeps its own spelling and only gains the new aliases. WHAT IT WILL NOT DO: it installs nothing, touches no other term, and does not guess the canonical -- pass the spelling exactly as the user writes it. Omit `aliases` and likely STT misspellings are generated for you, which beats inventing your own; show the user what was generated so they can veto one.

NameTypeReqDescription
aliasesarray–Spellings STT actually produces for this term. Omit to auto-suggest.
canonicalstringyesThe correct spelling, exactly as the user wants it written.
categorystring––
neverarray–Ordinary words that must never be rewritten to this term even if they sound alike, e.g. ["sauce"] for SaaS.
notesstring–Free text shown to agents, e.g. "my company; never write Ashlar".
phoneticstring–Pronunciation hint, e.g. "ASH-ler".
scopestring–'global' (default, ~/.config/lexicon) or 'project' (.lexicon.yaml in the current repo).

No output schema declared.

No examples provided.

apply_suggestion ~105

Apply a suggestion returned by suggest_terms after the user accepted it: 'alias' merges the alias into the term, 'term' adds the term (aliases auto-suggested when none given), 'never' records the word as never-rewrite on the term, 'stale' removes the term. Pass the suggestion object back as received.

NameTypeReqDescription
scopestring–Where to write: 'global' (default) or 'project'.
suggestionobjectyes–

No output schema declared.

No examples provided.

export_lexicon ~124

Export the merged lexicon in a format for another tool: 'claude-md' (markdown for CLAUDE.md / system prompts), 'markdown', 'text', 'wispr', 'superwhisper', 'whisper-prompt', 'openai', 'macos', 'espanso', 'deepgram', 'assemblyai', 'azure', 'google', 'csv', or raw 'json'.

NameTypeReqDescription
categoriesarray–Only include these categories.
formatstringyes–
limitinteger–Cap the number of terms exported.

No output schema declared.

No examples provided.

harvest_repo ~287

Scan a repository for proper nouns an STT engine is likely to mangle: package and dependency names, git authors, README brands, the project directory. Only names the repo says somewhere other than its own source are proposed: a class that exists nowhere but code is something the user types, not something they say, and adding it teaches the lexicon to rewrite ordinary dictation. WHEN TO CALL: when you are in a repo with no .lexicon.yaml and the user dictates about it, or when they ask what this project would add. Call it without `add` first -- that is a read-only preview. WHAT IT CHANGES: nothing unless `add: true`, which writes the candidates into the repo's .lexicon.yaml and trusts that file. That is a write inside the user's repository plus a trust decision, so show the candidate list and get a yes first. WHAT IT WILL NOT DO: it does not touch the global lexicon, and it does not pull file contents into the conversation -- candidates come back as names, categories and counts.

NameTypeReqDescription
addboolean–When true, add every candidate to the project lexicon.
limitinteger–Max candidates to return (default 50).
minCountinteger–Minimum occurrences for a candidate (default 2).
pathstring–Repository root. Defaults to the server working directory.

No output schema declared.

No examples provided.

import_dictionary ~208

Import a dictionary the user already has (Wispr Flow CSV, Superwhisper JSON, macOS Text Replacement plist, espanso YAML, plain text 'Canonical: alias1, alias2', generic CSV, or a lexicon JSON/YAML) into the lexicon. Pass either path (a file on disk, resolved from the server working directory) or content (the text itself, up to 8 MB). Use dryRun: true first to show the user what would be added, then run again without it.

NameTypeReqDescription
contentstring–The dictionary text, when the file is not on this machine.
dryRunboolean–Report what would be added without writing.
formatstring–Input format; 'auto' (default) sniffs it.
pathstring–File to import. Its extension helps auto-detection.
scopestring–'global' (default) or 'project' (.lexicon.yaml in the current repo).

No output schema declared.

No examples provided.

install_client ~187

Register the lexicon MCP server (and, for Claude Code, its hooks) in an agent client's config: claude, codex, cursor, windsurf, gemini, vscode or claude-desktop. Call with apply omitted (or false) first: that is a preview that returns the exact file and entry that would change and writes nothing. Show the preview to the user and call again with apply: true only after they confirm. Idempotent: an entry that is already present is left alone.

NameTypeReqDescription
applyboolean–false/omitted = preview only (default). true = write the config after the user confirmed.
clientstringyesWhich client to configure.
scopestring–'user' (default: the user-level config) or 'project' (the config inside the current repo, e.g. ./.cursor/mcp.json).

No output schema declared.

No examples provided.

learn_correction ~271

Record that the user corrected a spelling: they meant `meant`, but the transcript or you wrote `heard`. WHEN TO CALL: the moment the user corrects a name -- "it's Ashlr.AI not Ashler", "I said Hetzner", or they simply retype a name you got wrong. Call it while you reply. Do not ask permission for this one: it is the user's own correction being written down, and asking every time is the irritating version of this product. WHAT IT CHANGES: adds `heard` as an alias of `meant`, creating the term if it is new. One term; nothing else is touched. WHAT IT WILL NOT DO: it does not rewrite the message you already sent, and it cannot help if you hand it a whole phrase -- pass only the misspelled name as `heard`, not the sentence around it. Then get on with what the user actually asked for.

NameTypeReqDescription
heardstringyesThe wrong form that was written, e.g. "Ashler".
meantstringyesThe spelling the user wants, e.g. "Ashlr.AI".
scopestring–'global' (default; or wherever the term already lives) or 'project' (.lexicon.yaml in the current repo).

No output schema declared.

No examples provided.

lexicon_doctor ~378

Answers "is lexicon set up for this user, and what is the one command that fixes it" in a single call. WHEN TO CALL: when corrections are not happening, when the user asks whether it is set up, or before you offer to set it up, so you know whether there is anything to offer. Safe and free to call unprompted: it only reads. WHAT IT CHANGES: nothing. It writes no files and installs nothing. READ THESE THREE FIELDS FIRST: `ready` (boolean: true means corrections will actually happen for this user -- there are terms and an agent is wired up to use them), `summary` (one sentence, safe to relay verbatim) and `nextStep` (the single thing to do next, already phrased as an instruction; always present, and when nothing is broken it tells the user how to try it). If ready is true and the user only asked whether it works, `summary` alone is the whole answer -- do not paste the checks. ready being false does not always mean "not set up yet": a lexicon file that exists but does not parse also reports ready false, and `lexicon setup` will not repair it. Always relay `nextStep` as written instead of assuming setup is the fix; for an unreadable lexicon it names the file and points at `lexicon edit`. Also returns `ok` (no failing checks, which is weaker than `ready`: a lexicon with no terms fails nothing), `checks: [{ level: 'ok'|'warn'|'fail'|'info', message }]`, `paths` and `versions`. Read `checks` only when the user asks for detail or you need to diagnose something `nextStep` does not cover; warns are usually optional extras, not problems.

Input schema present but exposes no named parameters.

No output schema declared.

No examples provided.

lexicon_stats ~39

Counts of terms and aliases, total hits, the most-used terms, terms that never fired, and a per-file breakdown of the merged lexicon.

Input schema present but exposes no named parameters.

No output schema declared.

No examples provided.

list_packs ~79

List the starter packs shipped with the lexicon (developer, ai, business, voice-tools: curated names with the misspellings STT produces for them) and which are already installed. Call when onboarding a new user or when they ask what packs exist; describe each pack in one line, then call add_pack only for the ones they pick.

Input schema present but exposes no named parameters.

No output schema declared.

No examples provided.

list_terms ~159

List the user's lexicon terms, global and project merged. Optional case-insensitive substring filter over canonical spellings and aliases, plus a category filter. WHEN TO CALL: to show the user what is already known, to check whether a name is covered before adding it, or to find the exact canonical another tool needs. Read-only and safe to call unprompted; filter rather than listing everything. WHAT IT CHANGES: nothing. WHAT IT WILL NOT DO: it does not include an untrusted project .lexicon.yaml -- if one was skipped the result says so in `note`, and trust_project is how the user reviews it.

NameTypeReqDescription
categorystring––
querystring–Case-insensitive substring matched against canonical and aliases.

No output schema declared.

No examples provided.

normalize_transcript ~369

Fix the proper nouns speech-to-text got wrong, using this user's personal lexicon of names, brands, acronyms and identifiers. WHEN TO CALL: on any user message that looks dictated, before you act on it. Signs a message was dictated: run-on sentences with little punctuation, spoken filler ('um', 'so yeah'), homophone errors, no code or paths, or a capitalized word that is nearly a real name but not quite ('Ashler', "Cooper Nettie's", 'pie dentic'). One garbled proper noun is reason enough. You do not need the user to say they dictated it, and you do not need permission: this reads a file the user wrote and returns text. WHAT IT CHANGES: nothing the user can see. It does not edit their message, any file, or the lexicon; it only bumps a per-term hit counter. Use the `output` field as the message you act on, and mention the correction only if it changes what you are about to do. WHAT IT WILL NOT DO: it never rewrites text inside code blocks, inline code, file paths, URLs or emails, and it never invents a term that is not in the lexicon. If a word still looks garbled after this, call suggest_canonical rather than guessing. Returns { output, changed, replacements, summary }; when `changed` is false the text was already correct and you should carry on silently.

NameTypeReqDescription
dryRunboolean–When true, report candidate replacements without applying them (output === input).
minConfidencenumber–Override the minimum confidence (0..1) a fuzzy/phonetic match needs. Exact alias matches are always 1.
textstringyesThe dictated or transcribed text to correct.

No output schema declared.

No examples provided.

remove_term ~159

Delete a term from the user's lexicon by canonical spelling (case-insensitive). WHEN TO CALL: only when the user asks for a name to be forgotten, or after they accepted a 'stale' suggestion from suggest_terms. Never tidy the lexicon on your own initiative. WHAT IT CHANGES: removes that one term, and the corrections it was making stop happening. There is no undo through this server. WHAT IT WILL NOT DO: it does not touch any other term and will not remove a term you cannot name exactly -- use list_terms first if you are unsure which canonical the user means.

NameTypeReqDescription
canonicalstringyes–
scopestring–Which lexicon file to remove it from. Defaults to the store's resolution order.

No output schema declared.

No examples provided.

serve_status ~82

Check whether the local lexicon API (`lexicon serve`, used by the browser extension, Claude Desktop, Shortcuts and the menu bar app) is running on 127.0.0.1:41733. Returns { up: true, version, terms, ... } or { up: false }. Call when a non-MCP surface is not correcting text.

Input schema present but exposes no named parameters.

No output schema declared.

No examples provided.

setup_lexicon ~558

One-shot onboarding: seed the lexicon with the user's company and name, register the MCP server and hooks in their agent clients, optionally harvest the repo and install the local API as a login service. Ask the user for their company/product spelling, their own name, and which agent clients they use (claude, claude-desktop, codex, cursor, windsurf, gemini, vscode), then call this. Preview by default. Call once without apply to get the plan, show it to the user, then call again with apply: true, clients: [...] and serve: true only if the user agreed to each. The plan is { plan: true, lexiconPath, lexiconExists, wouldSeed, wouldInstallPacks, wouldHarvest, detectedClients, wouldInstallClients, wouldInstallServe, wouldExport } and is computed without writing anything. It writes the global lexicon and each named client's config. It does not install clients that are not listed (omitted = none; detectedClients in the plan tells you what to offer), does not install starter packs unless packs: [...] names them (wouldInstallPacks in the plan is the default set to offer; list_packs describes each), does not harvest the repo unless harvest: true (wouldHarvest in the plan is what to offer; harvest_repo previews the same names), and does not install the local API unless serve: true; offer those separately. Runs non-interactively and returns { ok, applied: true, summary }; tell the user what was installed and where the lexicon lives.

NameTypeReqDescription
applyboolean–false/omitted = preview only: return the plan and write nothing (default). true = perform the setup after the user confirmed the plan.
clientsarray–Agent clients to register the server in, exactly as the user agreed. Omitted or empty = none (the plan lists the detected ones so you can ask).
companystring–Company or product name, spelled exactly as it should appear.
harvestboolean–true = also add the repo names in wouldHarvest to the project .lexicon.yaml (and trust it). Only after the user agreed; omitted = not harvested.
packsarray–Starter packs to install into the global lexicon (developer, ai, business, voice-tools), exactly as the user agreed. Omitted or empty = none (the plan lists the defaults in wouldInstallPacks so you c…
personstring–The user's own name as they write it.
serveboolean–true = also install the local API (`lexicon serve`) as a login service. Only after the user agreed; omitted = not installed.

No output schema declared.

No examples provided.

suggest_canonical ~190

Look up what a garbled word was probably meant to be. WHEN TO CALL: when normalize_transcript left a suspicious proper noun alone. It only matches above a confidence threshold, so a badly mangled name gets through unchanged; call this before guessing, and before asking the user an open question. WHAT IT CHANGES: nothing. It only reads the lexicon. WHAT IT WILL NOT DO: it will not decide for you. It returns ranked { canonical, confidence, aliases } candidates: above about 0.8 use the canonical and mention it in passing, below that ask "did you mean X?" and call learn_correction once the user confirms, so the next transcript needs no asking. No suggestions means the name is simply not in the lexicon yet: offer to add it with add_term.

NameTypeReqDescription
heardstringyesThe suspicious word or phrase as it appeared in the transcript.

No output schema declared.

No examples provided.

suggest_terms ~140

Propose new aliases, terms and never-words from the user's voice history, usage and repo. Call weekly or when the user asks how to improve corrections; present them and apply accepted ones with apply_suggestion (or add_term). Each suggestion has kind 'alias' (a misspelling to add to an existing term), 'term' (a new name), 'never' (a word wrongly rewritten), or 'stale' (a term that never fires), plus reason, confidence and evidence.

NameTypeReqDescription
cwdstring–Repository to scan for evidence. Defaults to the server working directory.
limitinteger–Max suggestions to return.

No output schema declared.

No examples provided.

trust_project ~206

Manage trust for a repo's .lexicon.yaml, which is merged only after the user approves it (it can inject text into every session). action 'status' returns the trust state plus a compact preview (canonicals, first alias, counts) of the file; 'trust' approves the file at its current content and returns the same preview; 'untrust' revokes it. Always call 'status' first, show the user the preview and ask; call 'trust' only after they say yes. Never trust a file the user has not seen. Use this instead of reading .lexicon.yaml yourself: the preview passes every string through sanitizeForDisplay and reports notes as present without quoting them, so nothing the file says reaches the conversation as text. Do not open the file with Read or cat.

NameTypeReqDescription
actionstringyes–
pathstring–Lexicon file to act on. Defaults to the project .lexicon.yaml resolved from the server working directory.

No output schema declared.

No examples provided.

Common questions

What is the Lexicon MCP server?

Lexicon is an MCP server listed in the public MCP registry as io.github.ashlrai/lexicon. Fixes the names and jargon speech-to-text gets wrong before your agent acts on a dictated prompt. This page covers its npm package (@ashlr/lexicon).

Is the Lexicon MCP server safe to use?

Lexicon scores 69 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 28 September 2026. It declares no install or post-install scripts. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

What tools does the Lexicon MCP server expose?

Lexicon exposes 19 tools: normalize_transcript, add_term, remove_term, list_terms, export_lexicon, and 14 more. Their descriptions and schemas cost roughly 4,051 tokens of context every time the server is loaded.

Is the Lexicon MCP server still maintained?

Lexicon is still listed as active in the MCP registry. We last reached this channel on 28 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.

What licence is the Lexicon MCP server under?

Lexicon declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.