Deep Research MCP vs Agenda Intelligence Md | AllMCPs
Side-by-Side Model Context Protocol Comparison
Deep Research MCP vs Agenda Intelligence Md
In-depth architectural comparison of the Deep Research MCP and Agenda Intelligence Md MCP servers. Compare execution transports, security boundaries, tool capabilities, quality scores, and ready-to-paste client installation snippets for Claude, Cursor, Windsurf, and VS Code.
At a Glance & Executive Verdict
Deep Research MCP
Research · Local stdio
Quality: 53/100 (Good) | Auth: API Key required
Agenda Intelligence Md
Research · Local stdio
Quality: 61/100 (Good) | Auth: No auth required
Verdict Summary: Choose Deep Research MCP if you need specialized Research tools running via a local process. Choose Agenda Intelligence Md if your workspace requires Research integration with local subprocess execution. Both servers can be configured concurrently in your client's mcpServers manifest.
Which MCP Server Should You Choose?
Choose Deep Research MCP when:
You need dedicated capabilities in the Research domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: API Key required (BYOK (Pay Provider Direct)).
You have access to required keys: RESEARCH_PROVIDER, RESEARCH_API_KEY, RESEARCH_BASE_URL, RESEARCH_MODEL, RESEARCH_TIMEOUT, RESEARCH_POLL_INTERVAL, OPENAI_API_KEY, GEMINI_API_KEY.
Primary tools included: Multi-provider deep research, OpenAI web search support, OpenAI Code Interpreter support.
Deep Research MCP is categorized under Research and uses a local stdio subprocess. In contrast, Agenda Intelligence Md belongs to Research using local stdio subprocess. Select Deep Research MCP when you need capabilities focused on research and Agenda Intelligence Md when you require tools for research.
Validate a caller-provided agenda brief against agenda-brief.schema.json. Use before running scoring, evidence audit, or publication steps to catch missing sections and schema drift. Pass the parsed brief object as brief_json. Returns validation status and schema errors only; it does not judge factual truth, retrieve sources, or improve the brief.
validate_evidence
Validate a caller-provided evidence pack against evidence-pack.schema.json. Use when you need to confirm that claims, evidence IDs, provenance fields, and optional source_category metadata are structurally usable by Agenda Intelligence. Pass the parsed evidence pack as evidence_json. Returns schema validity and errors; it does not verify whether evidence is true, current, or sufficient.
check_evidence_packet
Check a caller-provided evidence packet before human review. Use when an AI output declares claims, source IDs, optional verbatim quotes, and the full supplied source text. Returns packet_complete, source_review_required, or packet_incomplete per claim and overall, with broken references, quote mismatches, lexical-support gaps, unmatched numbers, and owner actions. Deterministic and local-text only: it does not retrieve sources, score source authority, assess factual truth, or authorize an action.
audit_claims
Validate a claim-level evidence audit and summarize support quality. Use after drafting or receiving a memo to check whether important claims point to evidence IDs with explicit support levels, uncertainty hooks, and risk-if-wrong notes. Pass audit_json matching evidence-audit.schema.json. Returns validity, support-level distribution, orphan evidence references, and unsupported-claim counts. It does not verify factual truth or source reputation.
get_protocol
Return packaged Agenda Intelligence protocol markdown. Use when an agent needs the reasoning contract, evidence-discipline rules, or operating instructions before producing strategic-risk analysis. Pass name='entrypoint' for the main protocol. Returns markdown text from the installed package; it does not analyze a question or validate user data.
list_lenses
List packaged regional and sector lens IDs available to Agenda Intelligence. Use before get_lens when an agent needs to discover which geography or sector reference packs can be loaded. Optionally filter by lens_type='regional' or 'sector'. Returns metadata only; it does not return full lens markdown or run analysis.
get_lens
Return the full markdown for one packaged regional or sector lens. Use after list_lenses when an agent needs the actual specialist context, such as the Central Asia/Caspian or sanctions lens, for a strategic-risk task. Pass lens_type and lens_id exactly as listed. Returns static markdown; it does not retrieve live events or decide which lens should be used.
source_plan
Return required source categories for a strategic-risk evidence pack. Use before collection or review to know which source types should be checked for a domain such as sanctions, elections, conflict, cyber, or energy. Pass the source category slug as category. Returns a checklist of must_check and optional source types; it does not search the web, fetch documents, or validate an evidence pack.
list_source_categories
List source requirement category slugs packaged with Agenda Intelligence. Use this first when you do not know which category to pass to source_plan or source_coverage. Returns category IDs and per-pack counts. Discovery only: it does not discover sources, validate coverage, or verify factual truth.
source_coverage
Diagnose whether an evidence pack covers the must_check source types for a category. Use after collecting evidence to find source gaps before relying on a memo. Pass evidence_json and optionally category; if category is omitted, the tool uses evidence_json.source_category. Returns matched and missing source types. It does not discover new sources, verify truth, or change validate_evidence results.
score_output
Score a before/after pair of agenda-analysis text with the bundled heuristic rubric. Use in evals or demos to compare whether an Agenda Intelligence rewrite improved structure, evidence labeling, uncertainty handling, and decision-readiness. Pass before_text and after_text as plain strings. Returns a heuristic score and breakdown; it is not a factuality, legal, compliance, or investment judgment.
verify_quotes
Check whether quoted fragments appear in caller-provided source text. Use when you have local excerpts and need to catch citation drift or misquoted snippets. Accepts an evidence pack (sources/evidence items with a quote) or an evidence-audit doc with claims[].supporting_quotes; span checks carry the originating claim_id. Pass pack_json plus texts mapping evidence_id to plain text. Returns present, absent, and missing_source_text results. Local-text only: it does not make outbound requests, discover sources, score source reputation, gather news, or verify factual truth.