"Troubleshooting JavaScript Code" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Getting Things Done (GTD) board for AI agents: capture to Inbox, next actions by context, projects, waiting-for, someday/maybe. Remote Streamable HTTP server with OAuth 2.1 login (passwordless email code). 16 tools + 4 prompts. Setup guide: https://gtdbrain.com/connect?source=glama
Collide is an MCP layer that keeps concurrent AI agents from stepping on each other in a shared codebase. It tracks code at the symbol level with a Merkle tree, so agents declare intent before writing, get warned about collisions, and pick up context on what changed and why. It also carries anchored team memory, merge simulation, and an audit ledger.
Coding agents in multi-service codebases routinely rebuild existing helpers, trust stale type definitions, and modify API contracts without knowing who consumes them. Carrick solves this by indexing your entire TypeScript ecosystem across service and repository boundaries. By integrating deeply with the TypeScript compiler, Carrick traces every route, type, and cross-service call while recording function behaviour so agents search by intent rather than name. Delivered via MCP for AI agents and LSP for IDEs, Carrick ensures models see existing endpoints and utilities before generating new code. The scanner is source-available and runs from your CLI or CI pipeline.
App Store & Google Play keyword ranks, rivals, reviews, charts and AI visibility as an MCP server
Create, edit, read and review web presentations: slides, linked buttons, pictures, runnable code.
301SocialFaktory (https://www.socialfaktory.com) is a social media MCP server that lets your AI agent run a brand's social content with you. It reads the brands, channels and media you already have, writes posts in the brand's own voice, prices and generates short video, takes a file you upload, composes one post per channel, schedules or sends it on TikTok, Instagram, YouTube, X, LinkedIn, Facebook and Pinterest, and reads the metrics back. It is a hosted remote server at https://www.socialfaktory.com/mcp (Streamable HTTP) with OAuth 2.1 sign-in and 20 tools. Install steps cover Claude Code, Claude Desktop, Cursor, VS Code, Codex CLI, Gemini CLI and Windsurf. You stay in control. Generating spends the credits in your wallet, and the agent is told to quote the price and ask you first. Posts are drafts until you send them, and nothing reaches a channel without the publish permission you grant on the consent screen, where you also pin the connection to one brand, cap monthly spend and choose when it expires. Generating and publishing need an active SocialFaktory plan. Not available through an agent yet: cloning a video from a link, and generating still images or carousels. Connecting a social channel is a browser sign-in and stays in the app. Docs: https://www.socialfaktory.com/docs/mcp
Visual website builder synced with real code. Build, publish and maintain websites from any agent.
Talk to your own gym log. Reps is a free workout tracker for iPhone and Android; connect it to Claude, ChatGPT or any MCP client and ask about your workout history, personal records, exercise progression, weekly summaries, routines and training plan. The assistant can also save a new routine, edit one, save a whole plan, add custom exercises and exercise notes, always after you confirm in the chat. It cannot log a workout or delete your history. Requires a free Reps account created in the app; you sign in with a one-time email code.
Deploy JavaScript Functions and static sites, read logs, and roll back on wawesome.
Validate a product idea with real ad traffic from your coding agent. Create an idea, draft the brief and ad creative, and read the market read without leaving Claude Code, Codex, or OpenCode. 18 tools, all read-or-prepare; no tool can spend money. Docs: https://www.idea-launch.io/mcp
Parametric 3D CAD for AI agents. Claude Code, Cursor or any MCP client can build and edit real OwlCAD projects: primitives, booleans, and generators for gears, threads and Gridfinity. Check a part for printability and interference, then export STL, 3MF, OBJ or STEP. Output is an editable model with named millimetre dimensions, not a mesh, so you can open it in the browser and change any value afterwards. Sign in with OAuth or an access token. Requires OwlCAD Pro.
Whiteboard where any shape opens into another canvas. Claude Code and Codex plugins render plans on it.
Schedule and publish social media posts to 10 platforms from your AI agent
No-code app builder: manage your GoodBarber mobile app, shop, community and content. MCP 2026-07-28.
FFmpeg Micro MCP Server. Transcode videos from n8n or Make using FFmpeg in the cloud. Code+Docs: https://github.com/javidjamae/ffmpeg-micro-mcp/
Run Python code in a secure sandbox without local setup. Declare inline dependencies and execute s…
Search public open-source code, documentation, metadata, vulnerabilities, changelogs, and examples.
Compliance frameworks delivered to AI agents. Nizh gives your agent read access to your organization's compliance program — SOC 2, ISO 27001, CMMC 2.0, NIST, and more — as MCP tools, so it can check posture, read a control's objectives before changing code, and record where evidence lives.
# **RChilli MCP Hub** RChilli MCP Hub is a production-grade MCP server that exposes RChilli's full HR data intelligence platform as 17 AI-callable tools across 4 categories. Built on 15+ years of HR data intelligence, it is trusted by ATS vendors, HR technology platforms, staffing agencies, and enterprise recruiting teams worldwide. Every tool is read-only and returns a consistent, structured JSON response — no raw exceptions, no inconsistent formats. <br> --- <br> # **Tools — 17 Total** userkey and subuserid are injected automatically from your Bearer token — you never need to pass them manually. <br> --- <br> # **🔍 Resume & Job Description Parsing — 3 tools** <br> > ### **`extract_resume_data`** > > Extracts and converts resumes, CVs, and candidate documents into structured, searchable profiles with contact details, skills, experience, education, certifications, and taxonomy-enriched data for ATS, HCM, and AI recruiting workflows. When used on a careers page or application form, the same extraction call auto-fills every application field in under 10 seconds — documented to increase candidate conversion by up to 194%. Supports 40+ languages with English-normalized output for global intake, and runs in batch mode to process legacy databases or migration backlogs overnight at scale. Also supports resume reprocessing — re-running previously extracted resumes through the latest extraction logic and taxonomy version to bring older records up to current data quality, without requiring a new document from the candidate. Distinct from bulk import (first-time extraction of a new batch) and from talent data refresh (re-enrichment from a newer submitted resume). <br> > ### **`extract_resume_data_from_url`** > > Accepts a direct URL to a PDF, DOCX, or RTF file and returns the same normalized JSON profile as the Resume Data Extraction tool. Ideal for pipeline automation where resumes are stored in cloud storage, S3, or email attachments. Also supports the same auto-fill, multilingual, and batch-processing capabilities as the core extraction tool for URL-based intake sources. <br> > ### **`extract_job_data`** > > Extracts and converts job descriptions into structured hiring data including job title, required skills, preferred skills, responsibilities, experience, education, and taxonomy-normalized role requirements for recruitment automation and candidate matching. <br> --- <br> # **🧠 Skills & Job Taxonomy — 4 tools** <br> > ### **`lookup_skill`** > > Returns authoritative detail for a known skill including description, all aliases, related skills, proficiency levels, and O*NET/ESCO mappings. Use when you need the complete record rather than a ranked search. <br> > ### **`lookup_job_profile`** > > Returns authoritative detail for a known job profile including canonical title, SOC/O*NET code, job family, typical required and preferred skills, salary bands, and work context. <br> > ### **`autocomplete_skill`** > > Accepts a partial skill string (min 2 chars) and returns up to 10 ranked autocomplete suggestions with canonical names and categories. Prevents free-text entry errors and keeps skill data clean at point of entry. <br> > ### **`autocomplete_job_profile`** > > Accepts a partial job title string and returns ranked autocomplete suggestions with canonical titles and job families. Ensures job titles map to taxonomy profiles from the moment a recruiter starts typing. <br> --- <br> # **🛡️ Redaction, Documents & Utilities — 7 tools** <br> > ### **`redact_resume`** > > Redacts personally identifiable information from candidate profiles to support anonymized review, bias-aware screening, compliance workflows, and audit logs. Configurable redaction scope. Idempotent. <br> > ### **`reformat_resume_with_template`** > > RChilli's Resume Reformatting tool accepts any structured candidate profile and applies one of six branded templates (TM001–TM006) to produce a consistently formatted output document in PDF, DOCX, RTF, or HTML — ensuring every candidate is presented in a standardized, professional layout regardless of how their original resume was structured. Designed for staffing firms, recruitment agencies, and enterprise HR teams who need to control candidate presentation at scale, it eliminates manual reformatting effort and enforces brand consistency across all submissions. <br> > ### **`convert_document_format`** > > Accepts a document as base64 or URL and converts between PDF, DOCX, RTF, HTML, and plain text. Preserves formatting fidelity. Useful as a pre-processing step before data extraction on non-standard file types. <br> > ### **`tag_entities`** > > RChilli's Named Entity Recognition tool takes already-extracted HR text and annotates it by wrapping each recognized entity in a structured XML-style label inline — returning output such as `<job_title>Senior Data Engineer</job_title>`, `<skill>Python</skill>`, `<city>Austin</city>`, `<degree>Bachelor of Science</degree>`, and `<organization>Google</organization>` — covering 10+ HR-specific entity types including person name, state, country, date, and year. Unlike data extraction tools that produce separate field lists, tag_entities preserves the full original text structure with entities labeled in place, making the output immediately consumable by ATS field-mapping pipelines, candidate profile builders, and content annotation workflows without any offset calculation or post-processing. <br> > ### **`extract_contacts`** > > Identifies and structures names, emails, phone numbers, LinkedIn URLs, and addresses with field-level confidence scores from candidate records, emails, or documents. Safe for GDPR/CCPA workflows. <br> > ### **`geolocate`** > > Converts partial or informal location text into structured city, state, country, ISO codes, latitude, and longitude. Enables radius-based candidate and job search and supports workforce planning analytics. <br> > ### **`classify_job_zone`** > > RChilli's Job Zone Classification tool reads the job profile from a resume or job description and returns its O/*NET Job Zone — one of five standardized levels ranging from Zone 1 (little or no preparation required) through Zone 2 (some preparation), Zone 3 (medium preparation), Zone 4 (considerable preparation), to Zone 5 (extensive preparation required) — based on the education, experience, and training criteria defined by O/*NET. The returned Job Zone level enables downstream workflows such as candidate-to-role fit filtering, compensation benchmarking, over/under-qualification flagging, and job architecture standardization without any manual O/*NET lookup. <br> --- <br> # **🎯 Search & Matching — 3 tools** <br> > ### **`score_resume_against_jd`** > > Accepts one resume and one Job Description (no index required) and returns an overall match score, dimension scores, skill gap list, and natural-language explanation. Bias-controlled and audit-ready. <br> > ### **`find_matches_in_index`** > > Accepts a resume or Job Description as input and returns the top-N most similar documents from the indexed corpus ranked by semantic similarity. No index setup required for the input document. <br> > ### **`search_indexed_documents`** > > Accepts a query string and returns ranked document references from the tenant's pre-populated index. Supports Boolean and semantic search modes. Requires documents to be indexed before use.
Connect Claude, Cursor or any MCP client to AppSigma and let your AI research apps, read reviews and track rankings on its own – no glue code.
