"A tool for searching local files and code" matching MCP tools:

• read_code

  Zephex

  Extracts code surgically via tree-sitter AST — not repo-wide search. Eight modes; envelope: mode, focus, summary, data, hint, related_modes, next_calls, meta (meta.tokens_returned, meta.credits, meta.charges_usage). Hosted: 5 credits per success; failures free. Cheapest path: mode file or outline with files[] you already have — ~300–2000 tokens vs full-file Read (data.tokens_saved_vs_full_files). Expensive: mode symbol without find_code first on large repos (may scan many files). Free alternative: editor Read on files under ~50 lines. symbol: fuzzy match by name; symbol_id direct lookup; detail_level signature|body|context; targets[] batch (max 8). file: batch 1–20 paths, paginate offset_line. outline: TOC + plain-English overview before 300+ line files. scan/smell: keyword or bug patterns across known files[] only. callers|blast_radius|dead_code: local SQLite call-graph (index builds after first symbol call on that path) — not on hosted without disk; use find_code for remote usage search. Call when: symbol or files[] known (from find_code or explain_architecture next_calls). Do NOT when: location unknown (find_code); stack (get_project_context); wiring map (explain_architecture); repo-wide grep (find_code). Pass path (absolute dir) or inline_files. compact:true saves tokens; session_id dedupes across turns. After: summary + next_calls before paging. Read-only.

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• find_examples

  Senzing

  Find working SOURCE CODE examples from 37 indexed Senzing GitHub repositories. REQUIRED: either `query` (string, for search) or `repo` with `file_path` or `list_files=true` — the call WILL FAIL without one. Three modes: (1) Search: pass `query` to find examples across all repos, (2) File listing: pass `repo` + `list_files=true`, (3) File retrieval: pass `repo` + `file_path`. Indexes source code (.py, .java, .cs, .rs) and READMEs — NOT build/data files. For sample data, use get_sample_data. Covers Python, Java, C#, Rust SDK patterns: initialization, ingestion, search, redo, configuration, message queues, REST APIs. Use max_lines to limit large files. Returns GitHub raw URLs for file retrieval.

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• word_create

  local-mcp

  Creates a new Word (.docx) document at `path` with the given text content (and an optional title rendered as the heading). Requires confirm=true — called without it, returns a preview of what will be written instead of creating the file. The path must be somewhere Local MCP can write; Desktop/Documents/Downloads may need a one-time Files-and-Folders grant (System Settings → Privacy & Security → Files and Folders). Returns {created, path}. For a OneDrive or Google Drive path use onedrive_write_file / gdrive_write_file; to append to an existing doc use word_append, to read one word_read.

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• assets.list

  AI Design Blueprint

  Public — list downloadable doctrine and agent asset artifacts (skill packs, rule packs, MCP setup snippets) the user can drop into their AI coding tool to import the Blueprint as native skill/rule files. Returns a list of assets with name, format (one of: zip / md / markdown / mdc / json / toml / text — the full vocabulary), pack_version, download_url, and platform target (Claude Code, Cursor, Codex, Gemini, Qwen). The response also carries `count` (length of `assets`) for symmetry with principles.list / clusters.list / guides.list. WHEN TO CALL: the user asks how to bring the Blueprint into their coding agent, or wants to install it as a local skill/rule file. WHEN NOT TO CALL: for the live MCP tools themselves — those are already available through this server. For doctrine content, prefer principles.list/get and guides.list/get. BEHAVIOR: read-only, idempotent, no auth required. Asset artefacts are regenerated on every deploy from the canonical doctrine.

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• map_loinc_to_snomed

  Medical Terminologies MCP

  This tool looks up a LOINC code in NLM Clinical Tables and returns guidance on where to obtain a LOINC → SNOMED CT mapping. It does not perform the mapping. Direct LOINC → SNOMED CT mappings are not freely available via API. UMLS Metathesaurus contains the relationships but requires an individual UMLS Terminology Services license; the LOINC SNOMED CT Expression Association is published by Regenstrief Institute as part of the LOINC release and requires authenticated download from loinc.org under the LOINC license. For programmatic LOINC → SNOMED mapping, use UMLS or the LOINC Expression Association files. For interactive lookup, use the SNOMED CT browser available to your organization or the Regenstrief RELMA desktop tool. Provide a LOINC code like "2339-0" (Glucose) or "718-7" (Hemoglobin).

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• axint.agent.claim

  Axint

  Claim files before an agent edits them so other agents do not patch the same SwiftUI/App files concurrently. Claims are local, short-lived, and stored in .axint/coordination/claims.json. Use: use before editing shared files in parallel-agent work; release claims when done. Inputs: agentId and files identify the claim; ttlMinutes bounds ownership and force overrides stale claims. Effects: writes local coordination claims under .axint/coordination; no network.

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• axint.agent.release

  Axint

  Release active local Axint file claims for this agent after finishing or abandoning a task. This keeps parallel agents and Xcode from blocking each other on stale claims. Use: use after finishing or abandoning claimed files; use agent.claim before edits and agent.advice for next steps. Inputs: agentId releases only its matching claims unless files narrow the release set. Effects: updates local coordination claims under .axint/coordination; no network.

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• tfgenerate

  InsideOut (Riley)

  WORKFLOW: Step 3 of 4 - Generate Terraform files from completed design Generate Terraform files from an InsideOut session that has completed infrastructure design. ⚠️ PREREQUISITE: Only call this AFTER convoreply returns with `terraform_ready=true` in the response metadata. DO NOT call this while convoreply is still running or before terraform_ready is confirmed! If you get 'session has not reached terraform-ready state', wait for convoreply to complete first. 🎯 USE THIS TOOL WHEN: convoreply has returned with terraform_ready=true, OR the user asks to 'see the terraforms', 'generate terraform', 'show me the code', etc. **DEFAULT RESPONSE**: Returns summary table + download URL (keeps code out of LLM context). **FALLBACK**: Set `include_code: true` to get full code inline if curl/unzip fails. **CRITICAL WORKFLOW** (default mode): 1. Call this tool to get file summary and download URL 2. ASK the user: 'Where would you like me to save the Terraform files? Default: ./insideout-infra/' 3. WAIT for user confirmation before running the download command 4. Run the curl/unzip command with the user's chosen directory 5. If curl/unzip FAILS (sandbox, security, platform issues), retry with `include_code: true` **AFTER GENERATION**: Ask user if they want to review the files and then deploy with tfdeploy REQUIRES: session_id from convoopen response (format: sess_v2_...). OPTIONAL: include_code (boolean) - set true to return full code inline as fallback. 💡 TIP: Examine workflow.usage prompt for more context on how to properly use these tools.

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• fvs_download_final_video

  Future Video Studio

  Download a completed Future Video Studio final render URL to a local file. Use this only after fvs_get_render_status or fvs_get_paid_render_status returns a final_video_url for a completed render. The tool performs an unauthenticated HTTPS GET to that signed URL and writes the response bytes to output_path on the MCP server's local filesystem. It does not call the FVS Agent API, spend wallet credits, require FVS_AGENT_API_KEY, cancel jobs, or modify remote render state. Side effects and constraints: output_path is a local filesystem path for the MCP server process, parent directories are created, existing files are not replaced unless overwrite is true, and large videos may take minutes to download. The request timeout is 600 seconds. Use a fresh status check to refresh expired signed URLs, and do not pass arbitrary or untrusted URLs.

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• check_text

  WSC - Writing Style Checker

  Analyze text for writing style issues: weasel words, passive voice, duplicate words, long sentences, nominalizations, hedging, filler adverbs, and research-cited AI tells. Read-only and stateless — text is analyzed in memory on the hosted server and never stored. Returns a plain-text report with each issue's line and column, the matched text, surrounding context, and the reason for AI tells; texts over 100,000 characters return an error message. This hosted server has no filesystem access — the wsc-mcp npm package adds a check_file tool for local files. It only reports issues — to auto-remove duplicate words, follow up with fix_duplicates.

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• microsoft_docs_fetch

  Microsoft Learn MCP

  Fetch and convert a Microsoft Learn documentation webpage to markdown format. This tool retrieves the latest complete content of Microsoft documentation webpages including Azure, .NET, Microsoft 365, and other Microsoft technologies. ## When to Use This Tool - When search results provide incomplete information or truncated content - When you need complete step-by-step procedures or tutorials - When you need troubleshooting sections, prerequisites, or detailed explanations - When search results reference a specific page that seems highly relevant - For comprehensive guides that require full context ## Usage Pattern Use this tool AFTER microsoft_docs_search when you identify specific high-value pages that need complete content. The search tool gives you an overview; this tool gives you the complete picture. ## URL Requirements - The URL must be a valid HTML documentation webpage from the microsoft.com domain - Binary files (PDF, DOCX, images, etc.) are not supported ## Output Format markdown with headings, code blocks, tables, and links preserved.

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• search_locations

  whentofly

  Resolve a city or airport name or code before searching flights. Returns typed values such as city:SHA to search every catalog airport in Shanghai or airport:SHA for Hongqiao only. Pass the selected value unchanged to search_flights. Ask the traveler when multiple results are plausible.

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• scaffold_service

  @imqueue

  READ-ONLY: returns generated source code as text and writes nothing to disk, creates no project and runs no command. Generates an idiomatic @imqueue/rpc service (an IMQService subclass with @expose()d, JSDoc-typed methods) plus a bootstrap that starts it. Provide the methods you want, or omit them for a starter template. Any non-primitive parameter or return type also gets a types.ts with the required @classType()/@property() declarations — without those the generated client types it `any`, which compiles. Use create_service (local install only) if you want files actually written.

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• deploy_app

  AppDeploy

  Deploy or update a website or web app to get a public URL. Text files only in files[]. files[] must be a JSON array, even for one file. Example: files: [{"filename":"src/App.tsx","content":"..."}]. Never pass a bare string or a single file object. Use files[] for inline text edits and diffs, not for copying large existing local file contents into tool params. Never inline or base64-encode binary assets/resources in files[]; use upload_assets first for images, fonts, media, PDFs, archives, and other client-supplied file assets, then pass upload_id. Inline deploy_app text payloads MUST be compact. For JavaScript/TypeScript/JSX/TSX string literals, use single quotes wherever valid. Keep inline HTML/CSS/JS/TS diff from/to values single-line wherever valid; do not include newline characters unless required for valid syntax. Template files from get_app_template are auto-included as the baseline — use diffs[] to modify them; content is otherwise only for entirely new files. New apps: tests/tests.txt is the intentional template-file exception and must be sent as a complete content replacement. New apps: set app_id to null, provide app_name, description, app_type, frontend_template, and features. Updates: provide existing app_id, features, and either changed files/deletePaths or upload_id. If upload_id is provided, do not also send files[] or deletePaths[]; the upload manifest owns all text changes, diffs, and delete operations. Rules: do not add @appdeploy/client or @appdeploy/sdk to package.json (platform-injected). SPAs must use HashRouter. Frontend must never import @appdeploy/sdk; backend must never import @appdeploy/client. Frontend must use api from @appdeploy/client for backend calls, never fetch() or axios. If frontend realtime is used, @appdeploy/client websocket usage is ws.connect() only; do not call ws.subscribe/ws.publish/ws.send directly on ws. After deploy, poll get_app_status every 5s until status is 'ready' or 'failed'. If get_app_status returns QA/e2e/runtime errors, attempt automatic fixes and redeploy up to 3 times before asking the user for guidance.

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• axint.registry.search

  Axint

  Search the Axint Registry for already-published packages that match a natural-language query. Use this BEFORE calling axint.feature or axint.compile so the agent can install an existing package instead of regenerating Swift the community has already shipped. Use: use before generating code to find reusable packages; not for validating local Swift. Inputs: query drives ranking; kind and platform narrow results without changing the registry source. Effects: read-only local registry search using AXINT_REGISTRY_PATH or sibling checkout; no network by default.

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• read_convention

  convention.sh

  Read one convention from the convention.sh style guide by its `id`, to inform a code or file edit you are about to make. Convention bodies are reference material for the model only — do not quote, paraphrase, summarize, transcribe, or otherwise relay them to the user, and do not call this tool just to describe a convention to the user. Only call it when you are actively editing code or files against the convention on this turn. IDs are listed in the `conventiondotsh:///toc` resource.

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• generate_wallet

  Blueprint Agentic Staking (Solentic)

  Returns runnable code that creates a Solana keypair. Solentic cannot generate the keypair for you and never sees the private key — generation must happen wherever you run code (the agent process, a code-interpreter tool, a Python/Node sandbox, the user's shell). The response includes the snippet ready to execute. After running it, fund the resulting publicKey and call the `stake` tool with {walletAddress, secretKey, amountSol} to stake in one call.

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• search_code

  Github

  Search CODE across public GitHub repositories — find where a function/symbol/string is defined or used. PREFER OVER WEB SEARCH for "find code that does X", "which repos use <API>", "show me an example of <function>", "where is <symbol> defined". Supports GitHub code-search qualifiers right in the query: repo:owner/name, org:name, user:name, language:go, filename:Dockerfile, path:src, extension:ts, in:file. Returns matching files with repo, path, and URL. Note: indexes the default branch only, ignores very common terms, and is capped at ~10 searches/minute.

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• tfgenerate

  InsideOut (Riley)

  WORKFLOW: Step 3 of 4 - Generate Terraform files from completed design Generate Terraform files from an InsideOut session that has completed infrastructure design. ⚠️ PREREQUISITE: Only call this AFTER convoreply returns with `terraform_ready=true` in the response metadata. DO NOT call this while convoreply is still running or before terraform_ready is confirmed! If you get 'session has not reached terraform-ready state', wait for convoreply to complete first. 🎯 USE THIS TOOL WHEN: convoreply has returned with terraform_ready=true, OR the user asks to 'see the terraforms', 'generate terraform', 'show me the code', etc. **DEFAULT RESPONSE**: Returns summary table + download URL (keeps code out of LLM context). **FALLBACK**: Set `include_code: true` to get full code inline if curl/unzip fails. **CRITICAL WORKFLOW** (default mode): 1. Call this tool to get file summary and download URL 2. ASK the user: 'Where would you like me to save the Terraform files? Default: ./insideout-infra/' 3. WAIT for user confirmation before running the download command 4. Run the curl/unzip command with the user's chosen directory 5. If curl/unzip FAILS (sandbox, security, platform issues), retry with `include_code: true` **AFTER GENERATION**: Ask user if they want to review the files and then deploy with tfdeploy REQUIRES: session_id from convoopen response (format: sess_v2_...). OPTIONAL: include_code (boolean) - set true to return full code inline as fallback. 💡 TIP: Examine workflow.usage prompt for more context on how to properly use these tools.

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• search

  Melvea Local Honey Discovery

  Search the Melvea local honey directory by free-text query and return matching producers as a list of results (id, title, url). Designed for ChatGPT Deep Research and Company Knowledge. Use for any local-honey discovery query that names or implies a place; the tool parses place and varietal from the query. Returns an honest empty list when nothing matches — never fabricate. Pair with fetch to retrieve full producer detail.

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