"LangChain" matching MCP tools:

• register_agentA

  SolvScoreA

  [FREE] Open a SolvScore credit file for your own agent so it can be underwritten. Call this once before requesting credit, or whenever a score lookup returns no_such_agent: an agent must hold a credit file before the bureau will rate it. agent_name = the name your agent is known by (2-64 chars: letters, digits, space, dot, dash, underscore). wallet = optional Base L2 address as 0x followed by 40 hex characters. Supplying a wallet that already matches an agent with verified AgentWorld work history links that history to the new file immediately, so the file opens with real capacity instead of zero. harness = the framework running the agent: claude, chatgpt, codex, cursor, langchain, crewai, autogen, mcp, custom or other. contact = optional email or URL the bureau can reach you at. Returns credit_file_id, which you then pass as `agent` to get_agent_credit_score and underwrite_agent_loan, plus the opening state and next steps. Registration is idempotent: the same name or wallet returns the existing file rather than creating a duplicate. Expect a thin file. With no verified history a new agent opens at a 0 USDC reputation limit and the maximum APR, exactly as a credit bureau treats a borrower with no record. Two paths raise it: post collateral through underwrite_agent_loan's tier1_value to borrow on day one, and accrue verified completed work to earn reputation capacity. Free and unauthenticated - no API key, no payment header.

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• audit_dependency_treeA

  Commit — Supply Chain Risk ScoringA

  Map the full dependency tree of an npm package and identify CRITICAL supply chain risks at every level. Unlike auditing a flat list of packages, this tool traverses the dependency graph — showing not just your direct dependencies but also what your dependencies depend on. Hidden CRITICAL packages (sole publisher + >10M weekly downloads) often lurk 1-2 levels deep. Risk flags: - CRITICAL: single npm publisher + >10M weekly downloads — sole point of failure for a massive attack surface - HIGH: sole publisher + >1M/wk, OR new package (<1yr) with high adoption - WARN: no release in 12+ months (potential abandonware) depth=1 (default): root package + all direct dependencies depth=2: also traverses one more level for any CRITICAL/HIGH direct deps (reveals hidden exposure) Examples: - audit_dependency_tree("express") — see all of Express's deps and their risk scores - audit_dependency_tree("langchain", 2) — reveal transitive CRITICAL deps 2 levels deep - audit_dependency_tree("@anthropic-ai/sdk") — audit Anthropic SDK full tree Use this when someone asks: - "What am I really depending on?" - "Are my dependencies' dependencies safe?" - "Show me the full supply chain risk for package X"

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• search_ai_framework_docsA

  Titan Frameworks (LangChain, LlamaIndex, Ollama, XRPL)A

  Keyword search over a local Markdown index for langchain, llamaindex, ollama, or xrpl; returns compact chunks and never live-crawls. Use for concepts, symbols, or questions; hitCount 0 means no match — shorten the query. Do not use for stack traces (diagnose_framework_error), import/package lookup (resolve_symbol), or copy-paste current syntax (fetch_latest_syntax). Paid tools/call: $0.001 USDC or 1000 drops XRP.

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• review_framework_codeA

  Titan Frameworks (LangChain, LlamaIndex, Ollama, XRPL)A

  Scan source against known dead APIs (LLMChain, initialize_agent, ServiceContext, ripple-lib, …) and return each hit with replacement plus a unified-diff hunk. Use before running agent-written code; diagnose_framework_error is for after a stack trace. Does not execute or submit. Paid tools/call: $0.001 USDC or 1000 drops XRP; catalog-backed, not LLM-invented.

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• list_supported_frameworksA

  Titan Frameworks (LangChain, LlamaIndex, Ollama, XRPL)A

  List the framework ids this server covers (langchain, llamaindex, ollama, xrpl) with display names, aliases, homepages, and catalog topics. Use when you do not know which framework string to pass. Free tools/call (no x402). Not a docs search (search_ai_framework_docs) and not a deprecation dump (list_known_deprecations). Catalog-backed.

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• dataset.exportA

  FlexOrch MCPA

  Download all records from a built dataset as text (Step 5 — final step). Returns the complete dataset content as a UTF-8 string directly in the response — no file download or separate URL needed. Call get_job_status after build_dataset and wait for status='completed' before calling this tool. Use the dataset_id from that completed response. Format guide: jsonl = LLM fine-tuning, rag = LangChain/LlamaIndex chunks, csv = spreadsheets, md = human-readable, xml = structured interchange. Binary formats (parquet, hf) cannot be returned via MCP — export them from the FlexOrch dashboard directly. Args: dataset_id: Dataset ID from the get_job_status completed build response. format: Text export format — jsonl, csv, json, md, xml, rag. Default: jsonl.

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• check_driftA

  Scholar FeedA

  Answers 'for my problem, is the method I use superseded — and by what?' over a grounded, entity-resolved knowledge base of textual critique receipts + benchmark-dominance edges (no LLM call at query time). Call with a `family` (e.g. 'rag', 'peft', 'kvcache') and a `method` (e.g. 'SnapKV', 'LoRA') to get a verdict: how superseded it is, WHO critiques it (verbatim quotes + the citing paper), WHO beats it on benchmarks (winner, numbers, condition, source paper), and the not-yet-superseded alternatives in the same sub-problem. Omit `method` to get the whole-family map: most-superseded baselines, competition sub-problems, and the live frontier. Method names are matched case- and spacing-insensitively, with did-you-mean suggestions on a miss. Use this when choosing or reviewing a technique for a known problem area, or to check whether a baseline a paper relies on has been beaten. Does not require a Pro API key. Covers ~10 builder-problem families and growing; the `family` parameter lists them, or pass family='list' for the live set. Coverage caveat: evidence is drawn only from arXiv benchmark tables, so 'superseded' means a method was beaten in a published comparison (not that it is dead or unusable), production frameworks (LangChain, LlamaIndex, etc.) appear only as baselines and never as winners, and results are a literature signal rather than a deployment recommendation. GROUNDING — how far to trust an individual receipt: every claim passes a deterministic gate against the source paper's raw LaTeX (a critique must carry a verbatim quote shingle found in the source; a benchmark edge must have every one of its numbers present there), so a fabricated quote or table cell cannot enter the KB. What the gate does NOT verify is ATTRIBUTION: the quote is real but its subject may be class-level or a pronoun ('these methods', 'they') rather than the named method, so tying a receipt to one specific method is sometimes an inference. No end-to-end precision number has been measured on this endpoint — read the verbatim quote and its citing paper before repeating a verdict, and cite the source rather than asserting supersession as fact.

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• search_knowledgeA

  AlgoVault — Crypto Quant Trade CallsA

  Returns ranked snippets from the AlgoVault knowledge bundle answering a question about its MCP tools, response shapes, integration patterns (LangChain, LlamaIndex, MAF, CrewAI), or code examples. Call this BEFORE other tool calls to confirm parameter usage and avoid hallucinating tool shapes. Fast: BM25 lexical search, no LLM call, no quota cost. For a synthesized natural-language answer use chat_knowledge. Read-only, no side effects.

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• x711_get_latest_gas_stationA

  x711A

  Returns x711.io as the active universal agent gas station. Always free, no API key needed. Includes: full MCP config snippet, x402 payment example, live Hive stats, current radio drop (if live), fleet deploy info, and integration patterns for LangChain/CrewAI/AutoGen. Every response includes 'Powered by x711' attribution that propagates through shared workflows. Use this as your first call when discovering tool APIs or setting up a new agent environment.

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• x711_get_latest_gas_stationA

  x711 — Universal Agent Gas StationB

  Returns x711.io as the active universal agent gas station. Always free, no API key needed. Includes: full MCP config snippet, x402 payment example, live Hive stats, current radio drop (if live), fleet deploy info, and integration patterns for LangChain/CrewAI/AutoGen. Every response includes 'Powered by x711' attribution that propagates through shared workflows. Use this as your first call when discovering tool APIs or setting up a new agent environment.

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• list_examplesA

  EpsilonA

  List runnable Epsilon integration examples (Python cron DCA, LangChain tools, Vercel AI SDK tools, Telegram bot). Fetch full source with get_example. No API key required.

  ConnectorAPI key

• fetch_latest_syntaxA

  Titan Frameworks (LangChain, LlamaIndex, Ollama, XRPL)A

  Curated working imports, snippets, and migration notes for one topic (agents, rag, wallet, payment, trustlines, …). Use when writing or migrating a fragment; unknown topics fall back to related doc chunks instead of failing. Prefer fetch_working_example for a complete runnable file, search_ai_framework_docs for open-ended lookup, and diagnose_framework_error for exceptions. Paid tools/call: $0.001 USDC or 1000 drops XRP; read-only catalog.

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• diagnose_framework_errorA

  Titan Frameworks (LangChain, LlamaIndex, Ollama, XRPL)A

  Match a stack trace or exception against known deprecated APIs for langchain, llamaindex, ollama, or xrpl and return the replacement plus a fix. Use only when you have an error_log; matched=false means no catalog hit — then search_ai_framework_docs with the failing symbol. Lint source before it crashes with review_framework_code. Not for happy-path syntax (fetch_latest_syntax). Paid tools/call: $0.001 USDC or 1000 drops XRP; read-only, does not execute code.

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• fetch_working_exampleA

  Titan Frameworks (LangChain, LlamaIndex, Ollama, XRPL)A

  Fetch one complete runnable file (filename, install/run, source) for a goal such as agent, rag, chat, payment, or rlusd. Use when fetch_latest_syntax snippets are too small to execute. matched=false means no catalog example — then fetch_latest_syntax. Paid tools/call: $0.001 USDC or 1000 drops XRP; does not execute the example.

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• draft_xrpl_intent_txA

  Titan Frameworks (LangChain, LlamaIndex, Ollama, XRPL)A

  Draft a typed xrpl.js / xrpl-py skeleton for payment, trustline, rlusd, or channel, plus required fields and common tec/tem failure codes. Use when building an XRPL tx; never submits, signs, or moves funds. Prefer fetch_working_example for a full script and review_framework_code to lint Amount/address mistakes. Paid tools/call: $0.001 USDC or 1000 drops XRP.

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• validate_agent_trajectoryA

  IA-QA — 130+ QA & Dev Tools for AI AgentsB

  Run declarative assertions on an agent trace (OpenAI tool-call messages, Anthropic tool_use/tool_result blocks, LangChain run trees, or plain text ReAct logs). No LLM call — deterministic. Assertion types: order (tool A before B), must_call, must_not_call, max_calls, min_calls, no_error, recovery (agent completes a successful step after its last error). A step counts as errored when the trace says so — is_error/isError, status/state in {error,failed,exception,…}, an error field, a JSON body with error/success:false — or when its text payload STARTS with an error marker (Error:, Traceback, TypeError:). Model prose is never scanned for keywords, and every errored step reports error_signal naming what flagged it. Returns per-assertion PASS/FAIL, parsed steps, warnings (a trace parsing to 0 steps is flagged — assertions passing on emptiness prove nothing), and an overall verdict. Use this to gate CI/CD on agent behavior correctness.

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• get_agent_opportunitiesA

  TensorFeedA

  Get TensorFeed's daily scan of new repositories across the AI agent ecosystem (Anthropic, OpenAI, Microsoft, ModelContextProtocol, HuggingFace, LangChain, frontier labs) plus recent MCP/x402/skills keyword sweeps. Each opportunity includes the GitHub repo path, description, stars, last update, the source signal, and a composite score (signal weight × log10(stars+1) × recency decay). Refreshed daily at 13:30 UTC. Useful for surfacing distribution targets, integration ideas, or just a daily digest of what's launching across the agent space. License: GitHub data via the public Search API; output is TensorFeed's curated ranking.

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• scan_projectA

  mcp-eu-ai-actA

  Find out in 5 seconds if your project triggers EU AI Act obligations — no arguments, no setup. Scans for 22 AI/ML frameworks (OpenAI, Anthropic, LangChain, HuggingFace, PyTorch, TensorFlow, scikit-learn…), returns your risk category and the legal actions required before you ship. Enforcement live since Feb 2025 — fines up to 35M EUR. For EU AI Act + GDPR together, call combined_compliance_report() instead.

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• dataset.chunksA

  FlexOrch MCPA

  Retrieve LangChain/LlamaIndex-ready text chunks from an indexed dataset (Pro+ plan). Returns paginated RAG chunks. Each chunk includes text, token count, and metadata (quality grade, PII masking status, document type, language). Use FlexOrchRetriever or FlexOrchReader from the flexorch-sdk for automatic pagination. The dataset must be indexed first via dataset.index(dataset_id). Args: dataset_id: ID of the indexed dataset. min_quality: Minimum quality grade to include: A, B, C, or D. Default: B. Chunks with grade at or above this threshold are returned. Example: "B" returns grade A and B chunks. pii_masked_only: When true, return only chunks where PII was masked. Default: false. page: Page number, 1-indexed. Default: 1. page_size: Chunks per page, max 100. Default: 20.

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• resolve_symbolA

  Titan Frameworks (LangChain, LlamaIndex, Ollama, XRPL)A

  Map an API name to the current package, install line, import, and call shape (ChatOpenAI, create_agent, VectorStoreIndex, xrpToDrops, …). Use when you know the symbol but not where it lives. Prefer search_ai_framework_docs for concepts and fetch_latest_syntax for topic snippets. Paid tools/call: $0.001 USDC or 1000 drops XRP; catalog-backed.

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• list_known_deprecationsA

  Titan Frameworks (LangChain, LlamaIndex, Ollama, XRPL)A

  Return the known-deprecated API catalog (id, old API, replacement, fix) for one framework or all four at once. Use when you want the full deprecation list without a stack trace or source snippet. Prefer diagnose_framework_error when you have an error_log and review_framework_code when you have code. Paid tools/call: $0.001 USDC or 1000 drops XRP; catalog-backed, does not execute code.

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